Fig4_ATAC_peaks.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "aebae54a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.sparse import coo_matrix\n",
    "import bioframe as bf\n",
    "import bioframe.vis\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "from matplotlib import gridspec\n",
    "from matplotlib import cm\n",
    "from matplotlib.gridspec import GridSpec\n",
    "from matplotlib.gridspec import GridSpecFromSubplotSpec\n",
    "import matplotlib.colors as colors\n",
    "from matplotlib.colors import ListedColormap\n",
    "%matplotlib inline\n",
    "\n",
    "from collections import Counter\n",
    "import itertools\n",
    "import sys\n",
    "from collections import OrderedDict\n",
    "import random\n",
    "import seaborn as sns\n",
    "import scipy\n",
    "import pickle\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47f1609c-2f4f-4d57-825a-440372fd19c7",
   "metadata": {},
   "source": [
    "# call MACS3 peaks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "eece92c1-5d51-48be-962a-5f991c2abbaf",
   "metadata": {},
   "outputs": [],
   "source": [
    "#callpeak (narrow) shift and extend\n",
    "\n",
    "# bed='/Mp.reducedchroms.sorted.p4m5.sorted.bed'\n",
    "# outdir='/macs3peaks'\n",
    "# !bsub -q short -W 08:00 -n 4 -R \"span[hosts=1]\" -R \"rusage[mem=8000]\" \\\n",
    "#         \"macs3 callpeak -t $bed -g hs -f BED --nomodel --shift -75 --extsize 150 --name allM --outdir $outdir\"\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db001062-48f1-4a18-97dc-6898951256ba",
   "metadata": {},
   "source": [
    "# coverage at peaks: peakscov.py\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "1ce692a3-f085-4ac6-bb8a-f93f7cd7c9a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#peakscov.py\n",
    "\n",
    "# import bioframe\n",
    "# import pandas as pd\n",
    "# import numpy as np\n",
    "# import scipy\n",
    "# import sys\n",
    "# import os\n",
    "\n",
    "# arguments=sys.argv\n",
    "\n",
    "# directory=arguments[1]\n",
    "# cov=arguments[2]\n",
    "# peaks=arguments[3]\n",
    "# outdir=arguments[4]\n",
    "# logdir=arguments[5]\n",
    "\n",
    "# f = open(f'{logdir}/{cov}.log','w')\n",
    "# f.close()\n",
    "# f=open(f'{logdir}/{cov}.log','a')\n",
    "# f.write(\"go\\n\")\n",
    "# f.flush()\n",
    "\n",
    "# ##first cov\n",
    "# #files\n",
    "# cov_df=pd.read_csv(f'{directory}/{cov}/{cov}.genomcov.raw.bed',sep='\\t',names=['chrom','start','end','cov'])\n",
    "# peaks_df=pd.read_csv(f'{peaks}',sep='\\t',names=['chrom','start','end','Mscore','mGscore','pGscore'])\n",
    "# f.write(\"files in\\n\")\n",
    "# f.flush()\n",
    "\n",
    "# #overlap peaks with cov\n",
    "# peaks_cov=bioframe.overlap(peaks_df,cov_df,how='left',suffixes=('','_cov'))\n",
    "# f.write(\"overlap\\n\")\n",
    "# f.flush()\n",
    "\n",
    "# #calculate cov at peaks\n",
    "# cov_mat = peaks_cov.groupby(['chrom','start','end'])['cov_cov'].sum()\n",
    "\n",
    "# f.write(\"counts\\n\")\n",
    "# f.flush()\n",
    "\n",
    "# #save\n",
    "# cov_mat_df = cov_mat.reset_index()\n",
    "# cov_mat_df.to_csv(f'{outdir}/{cov}.out', sep='\\t', index=False)\n",
    "\n",
    "# f.write(\"fini\\n\")\n",
    "# f.close()\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "e4c2f35f-d9cd-4a79-8b75-08a22097be74",
   "metadata": {},
   "outputs": [],
   "source": [
    "#import os\n",
    "\n",
    "# #1\n",
    "# directory='/coverage/files'\n",
    "# #3\n",
    "# peaks='/union_R1R3_narrowPeaks_bothfirst_pmit.sorted.bed'\n",
    "# #4\n",
    "# outdir='/coverage/cov_allpeaks'\n",
    "# #5\n",
    "# logdir='/coverage/log'\n",
    "\n",
    "# for cov in os.listdir(directory):\n",
    "#     if os.path.isdir(os.path.join(directory,cov)):\n",
    "#         !bsub -q short -W 04:00 -n 4 -R \"span[hosts=1]\" -R rusage[mem=24000] \\\n",
    "#             \"source activate open2c2v2; python /coverage/peakscov.py {directory} {cov} {peaks} {outdir} {logdir}\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e0aef0c-e1e9-4318-9136-0e816c98ce0a",
   "metadata": {},
   "source": [
    "# Pooled peakset, keep ind replicate scores and overlap\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "9944063a-2fee-4679-bb67-e8c422de4ee7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <th>x</th>\n",
       "      <th>fc</th>\n",
       "      <th>-log10p</th>\n",
       "      <th>-log10q</th>\n",
       "      <th>s-s</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>820000</td>\n",
       "      <td>820432</td>\n",
       "      <td>pG_R2_peak_1</td>\n",
       "      <td>45</td>\n",
       "      <td>.</td>\n",
       "      <td>2.85412</td>\n",
       "      <td>6.51850</td>\n",
       "      <td>4.52402</td>\n",
       "      <td>106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>820495</td>\n",
       "      <td>821412</td>\n",
       "      <td>pG_R2_peak_2</td>\n",
       "      <td>60</td>\n",
       "      <td>.</td>\n",
       "      <td>3.10466</td>\n",
       "      <td>8.11686</td>\n",
       "      <td>6.05475</td>\n",
       "      <td>670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>821465</td>\n",
       "      <td>821724</td>\n",
       "      <td>pG_R2_peak_3</td>\n",
       "      <td>31</td>\n",
       "      <td>.</td>\n",
       "      <td>2.48880</td>\n",
       "      <td>5.02713</td>\n",
       "      <td>3.12693</td>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>822063</td>\n",
       "      <td>822247</td>\n",
       "      <td>pG_R2_peak_4</td>\n",
       "      <td>40</td>\n",
       "      <td>.</td>\n",
       "      <td>2.53061</td>\n",
       "      <td>6.03055</td>\n",
       "      <td>4.06223</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>826647</td>\n",
       "      <td>827978</td>\n",
       "      <td>pG_R2_peak_5</td>\n",
       "      <td>719</td>\n",
       "      <td>.</td>\n",
       "      <td>9.22495</td>\n",
       "      <td>75.61400</td>\n",
       "      <td>71.94060</td>\n",
       "      <td>853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141293</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22308249</td>\n",
       "      <td>22308493</td>\n",
       "      <td>pG_R2_peak_141294</td>\n",
       "      <td>27</td>\n",
       "      <td>.</td>\n",
       "      <td>2.70908</td>\n",
       "      <td>4.57909</td>\n",
       "      <td>2.70553</td>\n",
       "      <td>229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141294</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22370744</td>\n",
       "      <td>22371026</td>\n",
       "      <td>pG_R2_peak_141295</td>\n",
       "      <td>170</td>\n",
       "      <td>.</td>\n",
       "      <td>5.86968</td>\n",
       "      <td>19.38230</td>\n",
       "      <td>17.01960</td>\n",
       "      <td>139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141295</th>\n",
       "      <td>chrY</td>\n",
       "      <td>26403181</td>\n",
       "      <td>26403331</td>\n",
       "      <td>pG_R2_peak_141296</td>\n",
       "      <td>42</td>\n",
       "      <td>.</td>\n",
       "      <td>3.16060</td>\n",
       "      <td>6.24916</td>\n",
       "      <td>4.26521</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141296</th>\n",
       "      <td>chrY</td>\n",
       "      <td>26409089</td>\n",
       "      <td>26409292</td>\n",
       "      <td>pG_R2_peak_141297</td>\n",
       "      <td>54</td>\n",
       "      <td>.</td>\n",
       "      <td>3.46161</td>\n",
       "      <td>7.46185</td>\n",
       "      <td>5.42428</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141297</th>\n",
       "      <td>chrY</td>\n",
       "      <td>26410023</td>\n",
       "      <td>26410173</td>\n",
       "      <td>pG_R2_peak_141298</td>\n",
       "      <td>42</td>\n",
       "      <td>.</td>\n",
       "      <td>3.16060</td>\n",
       "      <td>6.24916</td>\n",
       "      <td>4.26521</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>141298 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom     start       end               name  score  x       fc  \\\n",
       "0       chr1    820000    820432       pG_R2_peak_1     45  .  2.85412   \n",
       "1       chr1    820495    821412       pG_R2_peak_2     60  .  3.10466   \n",
       "2       chr1    821465    821724       pG_R2_peak_3     31  .  2.48880   \n",
       "3       chr1    822063    822247       pG_R2_peak_4     40  .  2.53061   \n",
       "4       chr1    826647    827978       pG_R2_peak_5    719  .  9.22495   \n",
       "...      ...       ...       ...                ...    ... ..      ...   \n",
       "141293  chrY  22308249  22308493  pG_R2_peak_141294     27  .  2.70908   \n",
       "141294  chrY  22370744  22371026  pG_R2_peak_141295    170  .  5.86968   \n",
       "141295  chrY  26403181  26403331  pG_R2_peak_141296     42  .  3.16060   \n",
       "141296  chrY  26409089  26409292  pG_R2_peak_141297     54  .  3.46161   \n",
       "141297  chrY  26410023  26410173  pG_R2_peak_141298     42  .  3.16060   \n",
       "\n",
       "         -log10p   -log10q  s-s  \n",
       "0        6.51850   4.52402  106  \n",
       "1        8.11686   6.05475  670  \n",
       "2        5.02713   3.12693  156  \n",
       "3        6.03055   4.06223   79  \n",
       "4       75.61400  71.94060  853  \n",
       "...          ...       ...  ...  \n",
       "141293   4.57909   2.70553  229  \n",
       "141294  19.38230  17.01960  139  \n",
       "141295   6.24916   4.26521   58  \n",
       "141296   7.46185   5.42428  140  \n",
       "141297   6.24916   4.26521   70  \n",
       "\n",
       "[141298 rows x 10 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mMR1=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/mM_R1_peaks.narrowPeak', sep='\\t', names=['chrom','start','end','name','score','x','fc','-log10p','-log10q','s-s'], index_col=None)\n",
    "mMR3=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/mM_R2_peaks.narrowPeak', sep='\\t', names=['chrom','start','end','name','score','x','fc','-log10p','-log10q','s-s'], index_col=None)\n",
    "\n",
    "pMR1=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/pM_R1_peaks.narrowPeak', sep='\\t', names=['chrom','start','end','name','score','x','fc','-log10p','-log10q','s-s'], index_col=None)\n",
    "pMR3=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/pM_R2_peaks.narrowPeak', sep='\\t', names=['chrom','start','end','name','score','x','fc','-log10p','-log10q','s-s'], index_col=None)\n",
    "\n",
    "pMR1=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/pM_R1_peaks.narrowPeak', sep='\\t', names=['chrom','start','end','name','score','x','fc','-log10p','-log10q','s-s'], index_col=None)\n",
    "pMR3=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/pM_R2_peaks.narrowPeak', sep='\\t', names=['chrom','start','end','name','score','x','fc','-log10p','-log10q','s-s'], index_col=None)\n",
    "\n",
    "mGR1=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/mG_R1_peaks.narrowPeak', sep='\\t', names=['chrom','start','end','name','score','x','fc','-log10p','-log10q','s-s'], index_col=None)\n",
    "mGR3=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/mG_R2_peaks.narrowPeak', sep='\\t', names=['chrom','start','end','name','score','x','fc','-log10p','-log10q','s-s'], index_col=None)\n",
    "\n",
    "pGR1=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/pG_R1_peaks.narrowPeak', sep='\\t', names=['chrom','start','end','name','score','x','fc','-log10p','-log10q','s-s'], index_col=None)\n",
    "pGR3=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/pG_R2_peaks.narrowPeak', sep='\\t', names=['chrom','start','end','name','score','x','fc','-log10p','-log10q','s-s'], index_col=None)\n",
    "pGR3\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "78cf980c-898c-4cff-9b88-deea4007e130",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>826630</td>\n",
       "      <td>828066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>858687</td>\n",
       "      <td>859056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>866171</td>\n",
       "      <td>866515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>869443</td>\n",
       "      <td>870290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>875202</td>\n",
       "      <td>875737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159067</th>\n",
       "      <td>chrY</td>\n",
       "      <td>21845260</td>\n",
       "      <td>21846134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159068</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22263963</td>\n",
       "      <td>22264219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159069</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22265642</td>\n",
       "      <td>22266678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159070</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22370661</td>\n",
       "      <td>22371030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159071</th>\n",
       "      <td>chrY</td>\n",
       "      <td>26319533</td>\n",
       "      <td>26319755</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>159072 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom     start       end\n",
       "0       chr1    826630    828066\n",
       "1       chr1    858687    859056\n",
       "2       chr1    866171    866515\n",
       "3       chr1    869443    870290\n",
       "4       chr1    875202    875737\n",
       "...      ...       ...       ...\n",
       "159067  chrY  21845260  21846134\n",
       "159068  chrY  22263963  22264219\n",
       "159069  chrY  22265642  22266678\n",
       "159070  chrY  22370661  22371030\n",
       "159071  chrY  26319533  26319755\n",
       "\n",
       "[159072 rows x 3 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "allmerged=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/allpeaks_R1R3_merged_pooledM',\n",
    "                      sep='\\t',names=['chrom','start','end'])\n",
    "allmerged\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "d28c92ec-80bc-4251-b8a4-f864df36b102",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "159072 159072 159072\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>chrom_pG1</th>\n",
       "      <th>start_pG1</th>\n",
       "      <th>end_pG1</th>\n",
       "      <th>name_pG1</th>\n",
       "      <th>score_pG1</th>\n",
       "      <th>x_pG1</th>\n",
       "      <th>fc_pG1</th>\n",
       "      <th>-log10p_pG1</th>\n",
       "      <th>-log10q_pG1</th>\n",
       "      <th>s-s_pG1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>120664</th>\n",
       "      <td>chr4</td>\n",
       "      <td>71189569</td>\n",
       "      <td>71189799</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51550</th>\n",
       "      <td>chr14</td>\n",
       "      <td>106129362</td>\n",
       "      <td>106129639</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120659</th>\n",
       "      <td>chr4</td>\n",
       "      <td>71067770</td>\n",
       "      <td>71068062</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120658</th>\n",
       "      <td>chr4</td>\n",
       "      <td>71067396</td>\n",
       "      <td>71067708</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120657</th>\n",
       "      <td>chr4</td>\n",
       "      <td>71066841</td>\n",
       "      <td>71067292</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13788</th>\n",
       "      <td>chr1</td>\n",
       "      <td>224113757</td>\n",
       "      <td>224115108</td>\n",
       "      <td>chr1</td>\n",
       "      <td>224113910</td>\n",
       "      <td>224114811</td>\n",
       "      <td>pG_R1_peak_15782</td>\n",
       "      <td>1262.0</td>\n",
       "      <td>.</td>\n",
       "      <td>11.8681</td>\n",
       "      <td>134.284</td>\n",
       "      <td>126.261</td>\n",
       "      <td>181.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151951</th>\n",
       "      <td>chr7</td>\n",
       "      <td>124929304</td>\n",
       "      <td>124930380</td>\n",
       "      <td>chr7</td>\n",
       "      <td>124929408</td>\n",
       "      <td>124930275</td>\n",
       "      <td>pG_R1_peak_185153</td>\n",
       "      <td>1268.0</td>\n",
       "      <td>.</td>\n",
       "      <td>13.5870</td>\n",
       "      <td>135.087</td>\n",
       "      <td>126.881</td>\n",
       "      <td>537.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12656</th>\n",
       "      <td>chr1</td>\n",
       "      <td>206202844</td>\n",
       "      <td>206203880</td>\n",
       "      <td>chr1</td>\n",
       "      <td>206202852</td>\n",
       "      <td>206203866</td>\n",
       "      <td>pG_R1_peak_14400</td>\n",
       "      <td>1271.0</td>\n",
       "      <td>.</td>\n",
       "      <td>16.6223</td>\n",
       "      <td>135.425</td>\n",
       "      <td>127.195</td>\n",
       "      <td>329.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119551</th>\n",
       "      <td>chr4</td>\n",
       "      <td>39181940</td>\n",
       "      <td>39183567</td>\n",
       "      <td>chr4</td>\n",
       "      <td>39182050</td>\n",
       "      <td>39183514</td>\n",
       "      <td>pG_R1_peak_144399</td>\n",
       "      <td>1282.0</td>\n",
       "      <td>.</td>\n",
       "      <td>11.5976</td>\n",
       "      <td>137.101</td>\n",
       "      <td>128.218</td>\n",
       "      <td>311.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64841</th>\n",
       "      <td>chr17</td>\n",
       "      <td>15563019</td>\n",
       "      <td>15563929</td>\n",
       "      <td>chr17</td>\n",
       "      <td>15563104</td>\n",
       "      <td>15563917</td>\n",
       "      <td>pG_R1_peak_77391</td>\n",
       "      <td>1286.0</td>\n",
       "      <td>.</td>\n",
       "      <td>15.9647</td>\n",
       "      <td>138.102</td>\n",
       "      <td>128.617</td>\n",
       "      <td>392.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>159072 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        chrom      start        end chrom_pG1  start_pG1    end_pG1  \\\n",
       "120664   chr4   71189569   71189799         0          0          0   \n",
       "51550   chr14  106129362  106129639         0          0          0   \n",
       "120659   chr4   71067770   71068062         0          0          0   \n",
       "120658   chr4   71067396   71067708         0          0          0   \n",
       "120657   chr4   71066841   71067292         0          0          0   \n",
       "...       ...        ...        ...       ...        ...        ...   \n",
       "13788    chr1  224113757  224115108      chr1  224113910  224114811   \n",
       "151951   chr7  124929304  124930380      chr7  124929408  124930275   \n",
       "12656    chr1  206202844  206203880      chr1  206202852  206203866   \n",
       "119551   chr4   39181940   39183567      chr4   39182050   39183514   \n",
       "64841   chr17   15563019   15563929     chr17   15563104   15563917   \n",
       "\n",
       "                 name_pG1  score_pG1 x_pG1   fc_pG1  -log10p_pG1  -log10q_pG1  \\\n",
       "120664                  0        0.0     0   0.0000        0.000        0.000   \n",
       "51550                   0        0.0     0   0.0000        0.000        0.000   \n",
       "120659                  0        0.0     0   0.0000        0.000        0.000   \n",
       "120658                  0        0.0     0   0.0000        0.000        0.000   \n",
       "120657                  0        0.0     0   0.0000        0.000        0.000   \n",
       "...                   ...        ...   ...      ...          ...          ...   \n",
       "13788    pG_R1_peak_15782     1262.0     .  11.8681      134.284      126.261   \n",
       "151951  pG_R1_peak_185153     1268.0     .  13.5870      135.087      126.881   \n",
       "12656    pG_R1_peak_14400     1271.0     .  16.6223      135.425      127.195   \n",
       "119551  pG_R1_peak_144399     1282.0     .  11.5976      137.101      128.218   \n",
       "64841    pG_R1_peak_77391     1286.0     .  15.9647      138.102      128.617   \n",
       "\n",
       "        s-s_pG1  \n",
       "120664      0.0  \n",
       "51550       0.0  \n",
       "120659      0.0  \n",
       "120658      0.0  \n",
       "120657      0.0  \n",
       "...         ...  \n",
       "13788     181.0  \n",
       "151951    537.0  \n",
       "12656     329.0  \n",
       "119551    311.0  \n",
       "64841     392.0  \n",
       "\n",
       "[159072 rows x 13 columns]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#add peak scores for pooled and keep highest only\n",
    "mM1=bf.overlap(allmerged,mMR1,suffixes=('','_mM1'))\n",
    "mM1f=mM1.fillna(0).sort_values('score_mM1').drop_duplicates(subset=['chrom', 'start','end'], keep='last')\n",
    "\n",
    "mM3=bf.overlap(allmerged,mMR3,suffixes=('','_mM3'))\n",
    "mM3f=mM3.fillna(0).sort_values('score_mM3').drop_duplicates(subset=['chrom', 'start','end'], keep='last')\n",
    "\n",
    "pM1=bf.overlap(allmerged,pMR1,suffixes=('','_pM1'))\n",
    "pM1f=pM1.fillna(0).sort_values('score_pM1').drop_duplicates(subset=['chrom', 'start','end'], keep='last')\n",
    "\n",
    "pM3=bf.overlap(allmerged,pMR3,suffixes=('','_pM3'))\n",
    "pM3f=pM3.fillna(0).sort_values('score_pM3').drop_duplicates(subset=['chrom', 'start','end'], keep='last')\n",
    "\n",
    "mG1=bf.overlap(allmerged,mGR1,suffixes=('','_mG1'))\n",
    "mG1f=mG1.fillna(0).sort_values('score_mG1').drop_duplicates(subset=['chrom', 'start','end'], keep='last')\n",
    "\n",
    "mG3=bf.overlap(allmerged,mGR3,suffixes=('','_mG3'))\n",
    "mG3f=mG3.fillna(0).sort_values('score_mG3').drop_duplicates(subset=['chrom', 'start','end'], keep='last')\n",
    "\n",
    "pG1=bf.overlap(allmerged,pGR1,suffixes=('','_pG1'))\n",
    "pG1f=pG1.fillna(0).sort_values('score_pG1').drop_duplicates(subset=['chrom', 'start','end'], keep='last')\n",
    "\n",
    "pG3=bf.overlap(allmerged,pGR3,suffixes=('','_pG3'))\n",
    "pG3f=pG3.fillna(0).sort_values('score_pG3').drop_duplicates(subset=['chrom', 'start','end'], keep='last')\n",
    "\n",
    "\n",
    "print(len(mM1f),len(mG3f),len(pG3f))\n",
    "pG1f\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "5a85fb3d-6482-41d5-99b0-a9cf703e1d7a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "159072\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_mM1</th>\n",
       "      <th>score_pM1</th>\n",
       "      <th>score_mG1</th>\n",
       "      <th>score_pG1</th>\n",
       "      <th>score_mM3</th>\n",
       "      <th>score_pM3</th>\n",
       "      <th>score_mG3</th>\n",
       "      <th>score_pG3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr11</td>\n",
       "      <td>134171657</td>\n",
       "      <td>134171859</td>\n",
       "      <td>0.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr6</td>\n",
       "      <td>52336749</td>\n",
       "      <td>52336960</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr19</td>\n",
       "      <td>4273291</td>\n",
       "      <td>4273563</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr19</td>\n",
       "      <td>4281274</td>\n",
       "      <td>4281482</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr19</td>\n",
       "      <td>4313890</td>\n",
       "      <td>4314148</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159067</th>\n",
       "      <td>chr9</td>\n",
       "      <td>96883802</td>\n",
       "      <td>96884970</td>\n",
       "      <td>1246.0</td>\n",
       "      <td>1239.0</td>\n",
       "      <td>1472.0</td>\n",
       "      <td>1216.0</td>\n",
       "      <td>1054.0</td>\n",
       "      <td>853.0</td>\n",
       "      <td>1336.0</td>\n",
       "      <td>1103.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159068</th>\n",
       "      <td>chr16</td>\n",
       "      <td>55622436</td>\n",
       "      <td>55624006</td>\n",
       "      <td>1287.0</td>\n",
       "      <td>1193.0</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>1124.0</td>\n",
       "      <td>1093.0</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>1369.0</td>\n",
       "      <td>940.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159069</th>\n",
       "      <td>chr7</td>\n",
       "      <td>124929304</td>\n",
       "      <td>124930380</td>\n",
       "      <td>1336.0</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>1235.0</td>\n",
       "      <td>1268.0</td>\n",
       "      <td>1198.0</td>\n",
       "      <td>1074.0</td>\n",
       "      <td>1289.0</td>\n",
       "      <td>1210.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159070</th>\n",
       "      <td>chr7</td>\n",
       "      <td>25861697</td>\n",
       "      <td>25863276</td>\n",
       "      <td>1366.0</td>\n",
       "      <td>1304.0</td>\n",
       "      <td>1093.0</td>\n",
       "      <td>984.0</td>\n",
       "      <td>1182.0</td>\n",
       "      <td>1208.0</td>\n",
       "      <td>1112.0</td>\n",
       "      <td>1111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159071</th>\n",
       "      <td>chr1</td>\n",
       "      <td>206202844</td>\n",
       "      <td>206203880</td>\n",
       "      <td>1430.0</td>\n",
       "      <td>1362.0</td>\n",
       "      <td>1329.0</td>\n",
       "      <td>1271.0</td>\n",
       "      <td>1412.0</td>\n",
       "      <td>1275.0</td>\n",
       "      <td>1344.0</td>\n",
       "      <td>1224.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>159072 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        chrom      start        end  score_mM1  score_pM1  score_mG1  \\\n",
       "0       chr11  134171657  134171859        0.0       69.0      143.0   \n",
       "1        chr6   52336749   52336960        0.0        0.0      147.0   \n",
       "2       chr19    4273291    4273563        0.0        0.0        0.0   \n",
       "3       chr19    4281274    4281482        0.0        0.0       85.0   \n",
       "4       chr19    4313890    4314148        0.0        0.0       34.0   \n",
       "...       ...        ...        ...        ...        ...        ...   \n",
       "159067   chr9   96883802   96884970     1246.0     1239.0     1472.0   \n",
       "159068  chr16   55622436   55624006     1287.0     1193.0     1423.0   \n",
       "159069   chr7  124929304  124930380     1336.0     1300.0     1235.0   \n",
       "159070   chr7   25861697   25863276     1366.0     1304.0     1093.0   \n",
       "159071   chr1  206202844  206203880     1430.0     1362.0     1329.0   \n",
       "\n",
       "        score_pG1  score_mM3  score_pM3  score_mG3  score_pG3  \n",
       "0            37.0        0.0        0.0        0.0       48.0  \n",
       "1             0.0        0.0       41.0       76.0        0.0  \n",
       "2            50.0        0.0        0.0        0.0       40.0  \n",
       "3             0.0        0.0        0.0       68.0        0.0  \n",
       "4             0.0        0.0        0.0       26.0        0.0  \n",
       "...           ...        ...        ...        ...        ...  \n",
       "159067     1216.0     1054.0      853.0     1336.0     1103.0  \n",
       "159068     1124.0     1093.0     1068.0     1369.0      940.0  \n",
       "159069     1268.0     1198.0     1074.0     1289.0     1210.0  \n",
       "159070      984.0     1182.0     1208.0     1112.0     1111.0  \n",
       "159071     1271.0     1412.0     1275.0     1344.0     1224.0  \n",
       "\n",
       "[159072 rows x 11 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#1. union\n",
    "union=((mM1f.merge(pM1f,how='inner',on=['chrom','start','end'])).merge(mG1f,how='inner',on=['chrom','start','end'])).merge(pG1f,how='inner',on=['chrom','start','end'])\n",
    "union=union[['chrom','start','end','score_mM1','score_pM1','score_mG1','score_pG1']]\n",
    "union2=((mM3f.merge(pM3f,how='inner',on=['chrom','start','end'])).merge(mG3f,how='inner',on=['chrom','start','end'])).merge(pG3f,how='inner',on=['chrom','start','end'])\n",
    "union2=union2[['chrom','start','end','score_mM3','score_pM3','score_mG3','score_pG3']]\n",
    "union3=union.merge(union2,how='inner',on=['chrom','start','end'])\n",
    "#union3.to_csv('/union_pooledpeaks_withreps',sep='\\t', index=False, header=None)\n",
    "\n",
    "print(len(union3))\n",
    "union3\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "189cdbdd-b920-4967-bea9-2ecf8ce07461",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "98393\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_mM1</th>\n",
       "      <th>score_pM1</th>\n",
       "      <th>score_mG1</th>\n",
       "      <th>score_pG1</th>\n",
       "      <th>score_mM3</th>\n",
       "      <th>score_pM3</th>\n",
       "      <th>score_mG3</th>\n",
       "      <th>score_pG3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>41513</th>\n",
       "      <td>chr13</td>\n",
       "      <td>101271652</td>\n",
       "      <td>101272301</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>54.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41514</th>\n",
       "      <td>chr20</td>\n",
       "      <td>30631003</td>\n",
       "      <td>30631260</td>\n",
       "      <td>16.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41518</th>\n",
       "      <td>chr16</td>\n",
       "      <td>1048535</td>\n",
       "      <td>1048743</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41519</th>\n",
       "      <td>chr3</td>\n",
       "      <td>177615060</td>\n",
       "      <td>177615381</td>\n",
       "      <td>18.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41520</th>\n",
       "      <td>chr22</td>\n",
       "      <td>22032089</td>\n",
       "      <td>22032513</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159067</th>\n",
       "      <td>chr9</td>\n",
       "      <td>96883802</td>\n",
       "      <td>96884970</td>\n",
       "      <td>1246.0</td>\n",
       "      <td>1239.0</td>\n",
       "      <td>1472.0</td>\n",
       "      <td>1216.0</td>\n",
       "      <td>1054.0</td>\n",
       "      <td>853.0</td>\n",
       "      <td>1336.0</td>\n",
       "      <td>1103.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159068</th>\n",
       "      <td>chr16</td>\n",
       "      <td>55622436</td>\n",
       "      <td>55624006</td>\n",
       "      <td>1287.0</td>\n",
       "      <td>1193.0</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>1124.0</td>\n",
       "      <td>1093.0</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>1369.0</td>\n",
       "      <td>940.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159069</th>\n",
       "      <td>chr7</td>\n",
       "      <td>124929304</td>\n",
       "      <td>124930380</td>\n",
       "      <td>1336.0</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>1235.0</td>\n",
       "      <td>1268.0</td>\n",
       "      <td>1198.0</td>\n",
       "      <td>1074.0</td>\n",
       "      <td>1289.0</td>\n",
       "      <td>1210.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159070</th>\n",
       "      <td>chr7</td>\n",
       "      <td>25861697</td>\n",
       "      <td>25863276</td>\n",
       "      <td>1366.0</td>\n",
       "      <td>1304.0</td>\n",
       "      <td>1093.0</td>\n",
       "      <td>984.0</td>\n",
       "      <td>1182.0</td>\n",
       "      <td>1208.0</td>\n",
       "      <td>1112.0</td>\n",
       "      <td>1111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159071</th>\n",
       "      <td>chr1</td>\n",
       "      <td>206202844</td>\n",
       "      <td>206203880</td>\n",
       "      <td>1430.0</td>\n",
       "      <td>1362.0</td>\n",
       "      <td>1329.0</td>\n",
       "      <td>1271.0</td>\n",
       "      <td>1412.0</td>\n",
       "      <td>1275.0</td>\n",
       "      <td>1344.0</td>\n",
       "      <td>1224.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>98393 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        chrom      start        end  score_mM1  score_pM1  score_mG1  \\\n",
       "41513   chr13  101271652  101272301       16.0        0.0       41.0   \n",
       "41514   chr20   30631003   30631260       16.0       39.0       36.0   \n",
       "41518   chr16    1048535    1048743       18.0        0.0      113.0   \n",
       "41519    chr3  177615060  177615381       18.0       46.0      104.0   \n",
       "41520   chr22   22032089   22032513       18.0        0.0       70.0   \n",
       "...       ...        ...        ...        ...        ...        ...   \n",
       "159067   chr9   96883802   96884970     1246.0     1239.0     1472.0   \n",
       "159068  chr16   55622436   55624006     1287.0     1193.0     1423.0   \n",
       "159069   chr7  124929304  124930380     1336.0     1300.0     1235.0   \n",
       "159070   chr7   25861697   25863276     1366.0     1304.0     1093.0   \n",
       "159071   chr1  206202844  206203880     1430.0     1362.0     1329.0   \n",
       "\n",
       "        score_pG1  score_mM3  score_pM3  score_mG3  score_pG3  \n",
       "41513       104.0       26.0       47.0       52.0       54.0  \n",
       "41514         0.0       68.0        0.0       54.0       40.0  \n",
       "41518         0.0       44.0        0.0       75.0        0.0  \n",
       "41519         0.0       48.0       30.0      153.0        0.0  \n",
       "41520        19.0       39.0       42.0       63.0        0.0  \n",
       "...           ...        ...        ...        ...        ...  \n",
       "159067     1216.0     1054.0      853.0     1336.0     1103.0  \n",
       "159068     1124.0     1093.0     1068.0     1369.0      940.0  \n",
       "159069     1268.0     1198.0     1074.0     1289.0     1210.0  \n",
       "159070      984.0     1182.0     1208.0     1112.0     1111.0  \n",
       "159071     1271.0     1412.0     1275.0     1344.0     1224.0  \n",
       "\n",
       "[98393 rows x 11 columns]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#2. bookmarked\n",
    "bm=union3[(union3['score_mM1']>0)&(union3['score_mG1']>0)&(union3['score_mM3']>0)&(union3['score_mG3']>0)]\n",
    "bm=bm[['chrom','start','end','score_mM1','score_pM1','score_mG1','score_pG1','score_mM3','score_pM3','score_mG3','score_pG3']]\n",
    "#bm.to_csv('/bookmarked_pooledpeaks_reps_newest',sep='\\t', index=False, header=None)\n",
    "\n",
    "print(len(bm))\n",
    "bm\n",
    "#98393"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "76c4d57d-be74-44dd-a7ff-7cde3d509d1e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "27720\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_mM1</th>\n",
       "      <th>score_pM1</th>\n",
       "      <th>score_mG1</th>\n",
       "      <th>score_pG1</th>\n",
       "      <th>score_mM3</th>\n",
       "      <th>score_pM3</th>\n",
       "      <th>score_mG3</th>\n",
       "      <th>score_pG3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr6</td>\n",
       "      <td>52336749</td>\n",
       "      <td>52336960</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr19</td>\n",
       "      <td>4281274</td>\n",
       "      <td>4281482</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr19</td>\n",
       "      <td>4313890</td>\n",
       "      <td>4314148</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>chr19</td>\n",
       "      <td>4327360</td>\n",
       "      <td>4327585</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>chr11</td>\n",
       "      <td>133911262</td>\n",
       "      <td>133911506</td>\n",
       "      <td>0.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>444.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>361.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41504</th>\n",
       "      <td>chr5</td>\n",
       "      <td>91081396</td>\n",
       "      <td>91081671</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41505</th>\n",
       "      <td>chr9</td>\n",
       "      <td>78700034</td>\n",
       "      <td>78700311</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>241.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41506</th>\n",
       "      <td>chr3</td>\n",
       "      <td>189490466</td>\n",
       "      <td>189490648</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41507</th>\n",
       "      <td>chr9</td>\n",
       "      <td>79221158</td>\n",
       "      <td>79221393</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41508</th>\n",
       "      <td>chr10</td>\n",
       "      <td>35611849</td>\n",
       "      <td>35612015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>27720 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom      start        end  score_mM1  score_pM1  score_mG1  \\\n",
       "1       chr6   52336749   52336960        0.0        0.0      147.0   \n",
       "3      chr19    4281274    4281482        0.0        0.0       85.0   \n",
       "4      chr19    4313890    4314148        0.0        0.0       34.0   \n",
       "5      chr19    4327360    4327585        0.0        0.0       61.0   \n",
       "8      chr11  133911262  133911506        0.0      178.0      444.0   \n",
       "...      ...        ...        ...        ...        ...        ...   \n",
       "41504   chr5   91081396   91081671        0.0       43.0       94.0   \n",
       "41505   chr9   78700034   78700311        0.0       85.0      230.0   \n",
       "41506   chr3  189490466  189490648        0.0        0.0      115.0   \n",
       "41507   chr9   79221158   79221393        0.0        0.0      108.0   \n",
       "41508  chr10   35611849   35612015        0.0        0.0       66.0   \n",
       "\n",
       "       score_pG1  score_mM3  score_pM3  score_mG3  score_pG3  \n",
       "1            0.0        0.0       41.0       76.0        0.0  \n",
       "3            0.0        0.0        0.0       68.0        0.0  \n",
       "4            0.0        0.0        0.0       26.0        0.0  \n",
       "5            0.0        0.0        0.0       71.0        0.0  \n",
       "8            0.0        0.0        0.0      361.0        0.0  \n",
       "...          ...        ...        ...        ...        ...  \n",
       "41504        0.0        0.0        0.0       71.0        0.0  \n",
       "41505        0.0        0.0        0.0      241.0        0.0  \n",
       "41506        0.0        0.0       32.0       52.0        0.0  \n",
       "41507        0.0        0.0        0.0       77.0        0.0  \n",
       "41508        0.0        0.0        0.0      106.0        0.0  \n",
       "\n",
       "[27720 rows x 11 columns]"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#5. mG\n",
    "mg=union3[(union3['score_mM1']==0)&(union3['score_mG1']>0)&(union3['score_mM3']==0)&(union3['score_mG3']>0)]\n",
    "#mg.to_csv('/G1_pooledpeaks_reps_newest',sep='\\t', index=False, header=None)\n",
    "\n",
    "print(len(mg))\n",
    "mg\n",
    "#27720"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "5fcd9089",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "159072 142543\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chrY</td>\n",
       "      <td>26319533</td>\n",
       "      <td>26319755</td>\n",
       "      <td>0.0</td>\n",
       "      <td>342.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18090847</td>\n",
       "      <td>18091143</td>\n",
       "      <td>0.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18090171</td>\n",
       "      <td>18090345</td>\n",
       "      <td>0.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18077179</td>\n",
       "      <td>18077421</td>\n",
       "      <td>0.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18074675</td>\n",
       "      <td>18075141</td>\n",
       "      <td>0.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159067</th>\n",
       "      <td>chr16</td>\n",
       "      <td>22436440</td>\n",
       "      <td>22437926</td>\n",
       "      <td>1211.0</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>1108.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159068</th>\n",
       "      <td>chr16</td>\n",
       "      <td>15153921</td>\n",
       "      <td>15155441</td>\n",
       "      <td>1234.0</td>\n",
       "      <td>960.0</td>\n",
       "      <td>1064.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159069</th>\n",
       "      <td>chr15</td>\n",
       "      <td>90497848</td>\n",
       "      <td>90498397</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>1404.0</td>\n",
       "      <td>654.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159070</th>\n",
       "      <td>chr9</td>\n",
       "      <td>96883802</td>\n",
       "      <td>96884970</td>\n",
       "      <td>1254.0</td>\n",
       "      <td>1433.0</td>\n",
       "      <td>1168.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159071</th>\n",
       "      <td>chr1</td>\n",
       "      <td>206202844</td>\n",
       "      <td>206203880</td>\n",
       "      <td>1373.0</td>\n",
       "      <td>1373.0</td>\n",
       "      <td>1302.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>159072 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        chrom      start        end  score_M  score_mG  score_pG\n",
       "0        chrY   26319533   26319755      0.0     342.0       0.0\n",
       "1       chr20   18090847   18091143      0.0      61.0       0.0\n",
       "2       chr20   18090171   18090345      0.0      77.0       0.0\n",
       "3       chr20   18077179   18077421      0.0      64.0       0.0\n",
       "4       chr20   18074675   18075141      0.0     112.0       0.0\n",
       "...       ...        ...        ...      ...       ...       ...\n",
       "159067  chr16   22436440   22437926   1211.0    1003.0    1108.0\n",
       "159068  chr16   15153921   15155441   1234.0     960.0    1064.0\n",
       "159069  chr15   90497848   90498397   1250.0    1404.0     654.0\n",
       "159070   chr9   96883802   96884970   1254.0    1433.0    1168.0\n",
       "159071   chr1  206202844  206203880   1373.0    1373.0    1302.0\n",
       "\n",
       "[159072 rows x 6 columns]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "union=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/union_R1R3_narrowPeaks_bothfirst_pmit',sep='\\t',names=['chrom','start','end','score_M','score_mG','score_pG'])\n",
    "allG1=union[union['score_mG']>0]\n",
    "print(len(union),len(allG1))\n",
    "union\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "9fa413d8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/allana.schooley-umw/miniconda3/envs/open2c2v2/lib/python3.9/site-packages/upsetplot/plotting.py:795: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
      "\n",
      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
      "\n",
      "\n",
      "  styles[\"linewidth\"].fillna(1, inplace=True)\n",
      "/home/allana.schooley-umw/miniconda3/envs/open2c2v2/lib/python3.9/site-packages/upsetplot/plotting.py:796: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
      "\n",
      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
      "\n",
      "\n",
      "  styles[\"facecolor\"].fillna(self._facecolor, inplace=True)\n",
      "/home/allana.schooley-umw/miniconda3/envs/open2c2v2/lib/python3.9/site-packages/upsetplot/plotting.py:797: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
      "\n",
      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
      "\n",
      "\n",
      "  styles[\"edgecolor\"].fillna(styles[\"facecolor\"], inplace=True)\n",
      "/home/allana.schooley-umw/miniconda3/envs/open2c2v2/lib/python3.9/site-packages/upsetplot/plotting.py:798: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
      "\n",
      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
      "\n",
      "\n",
      "  styles[\"linestyle\"].fillna(\"solid\", inplace=True)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'matrix': <AxesSubplot: >,\n",
       " 'shading': <AxesSubplot: >,\n",
       " 'totals': <AxesSubplot: >,\n",
       " 'intersections': <AxesSubplot: ylabel='Intersection size'>}"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 577.778x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import pandas as pd\n",
    "from upsetplot import plot, from_indicators\n",
    "from upsetplot import generate_counts, UpSet\n",
    "\n",
    "updata=union[['score_M','score_mG','score_pG']].copy()\n",
    "\n",
    "updata['pro-metaphase']=updata['score_M']\n",
    "updata['control G1']=updata['score_mG']\n",
    "updata['ΔRanGAP1 G1']=updata['score_pG']\n",
    "\n",
    "updata=updata[['pro-metaphase','control G1','ΔRanGAP1 G1']]\n",
    "updata.replace(0, np.nan, inplace=True)\n",
    "\n",
    "updata=from_indicators(indicators=pd.notna, data=updata)\n",
    "upset = UpSet(updata,sort_by='cardinality',show_percentages=True)\n",
    "upset.style_subsets(present=['pro-metaphase'], facecolor=\"darkgoldenrod\", label=None,edgecolor='black',linewidth=0.5)\n",
    "upset.style_subsets(present=['control G1'], absent=['pro-metaphase','ΔRanGAP1 G1'],facecolor=\"royalblue\", label=None,edgecolor='black',linewidth=0.5)\n",
    "upset.style_subsets(present=['ΔRanGAP1 G1'], absent=['pro-metaphase'],facecolor=\"firebrick\", label=None,edgecolor='black',linewidth=0.5)\n",
    "upset.plot(fig = plt.figure(figsize=(13, 13)))\n",
    "#plt.suptitle(\"ATAC peaks\")\n",
    "#plt.savefig('/atacpeaks_all_upset_colours.pdf', bbox_inches = 'tight', dpi = 300)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "2e0f89bb-f6ea-4807-8de7-789e441113ed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2105 759 1390\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>sizemaybe</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>6590000</td>\n",
       "      <td>6620000</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>7760000</td>\n",
       "      <td>7790000</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>chr1</td>\n",
       "      <td>8080000</td>\n",
       "      <td>8110000</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>chr1</td>\n",
       "      <td>9130000</td>\n",
       "      <td>9160000</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>chr1</td>\n",
       "      <td>19890000</td>\n",
       "      <td>19920000</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2136</th>\n",
       "      <td>chr21</td>\n",
       "      <td>39610000</td>\n",
       "      <td>39650000</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2138</th>\n",
       "      <td>chr22</td>\n",
       "      <td>28830000</td>\n",
       "      <td>28860000</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2139</th>\n",
       "      <td>chr22</td>\n",
       "      <td>28890000</td>\n",
       "      <td>28920000</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2147</th>\n",
       "      <td>chr22</td>\n",
       "      <td>40000000</td>\n",
       "      <td>40050000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2148</th>\n",
       "      <td>chr22</td>\n",
       "      <td>44690000</td>\n",
       "      <td>44740000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1390 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      chrom     start       end  sizemaybe\n",
       "2      chr1   6590000   6620000      30000\n",
       "3      chr1   7760000   7790000      30000\n",
       "5      chr1   8080000   8110000      30000\n",
       "6      chr1   9130000   9160000      30000\n",
       "8      chr1  19890000  19920000      30000\n",
       "...     ...       ...       ...        ...\n",
       "2136  chr21  39610000  39650000      40000\n",
       "2138  chr22  28830000  28860000      30000\n",
       "2139  chr22  28890000  28920000      30000\n",
       "2147  chr22  40000000  40050000      50000\n",
       "2148  chr22  44690000  44740000      50000\n",
       "\n",
       "[1390 rows x 4 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import bioframe as bf\n",
    "\n",
    "cyt=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/nativecomps/240708_enrich/pCyto_2X_enrichment.pixel_derived.signal_fullpeaks.bed',\n",
    "               sep='\\t',names=['chrom','start','end','sizemaybe'])\n",
    "cyt['start_ext']=cyt['start']-5000\n",
    "cyt['end_ext']=cyt['end']+5000\n",
    "g1=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/nativecomps/240708_enrich/5hr_2X_enrichment.pixel_derived.signal_fullpeaks.bed',\n",
    "               sep='\\t',names=['chrom','start','end','sizemaybe'])\n",
    "g1['start_ext']=g1['start']-5000\n",
    "g1['end_ext']=g1['end']+5000\n",
    "\n",
    "cyt_g1=bf.overlap(g1,cyt,cols1=['chrom','start_ext','end_ext'],cols2=['chrom','start_ext','end_ext']).drop_duplicates().dropna(subset='start_')\n",
    "cyt_g1=cyt_g1[['chrom','start','end','sizemaybe']]\n",
    "g1_spec=bf.overlap(g1,cyt,cols1=['chrom','start_ext','end_ext'],cols2=['chrom','start_ext','end_ext'])\n",
    "g1_spec=g1_spec[g1_spec['start_'].isnull()].drop_duplicates()\n",
    "g1_spec=g1_spec[['chrom','start','end','sizemaybe']]\n",
    "\n",
    "print(len(g1),len(cyt_g1),len(g1_spec))\n",
    "g1_spec\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "ab6d27e1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7887 7594\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "      <th>chrom_</th>\n",
       "      <th>start_</th>\n",
       "      <th>end_</th>\n",
       "      <th>sizemaybe_</th>\n",
       "      <th>start_ext_</th>\n",
       "      <th>end_ext_</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18279312</td>\n",
       "      <td>18279628</td>\n",
       "      <td>0.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>18260000</td>\n",
       "      <td>18290000</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>18255000.0</td>\n",
       "      <td>18295000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18272520</td>\n",
       "      <td>18272764</td>\n",
       "      <td>0.0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>18260000</td>\n",
       "      <td>18290000</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>18255000.0</td>\n",
       "      <td>18295000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18263263</td>\n",
       "      <td>18264156</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1084.0</td>\n",
       "      <td>314.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>18260000</td>\n",
       "      <td>18290000</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>18255000.0</td>\n",
       "      <td>18295000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>chr9</td>\n",
       "      <td>112360232</td>\n",
       "      <td>112360692</td>\n",
       "      <td>0.0</td>\n",
       "      <td>237.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>chr9</td>\n",
       "      <td>112340000</td>\n",
       "      <td>112370000</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>112335000.0</td>\n",
       "      <td>112375000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>chr9</td>\n",
       "      <td>112348341</td>\n",
       "      <td>112348979</td>\n",
       "      <td>0.0</td>\n",
       "      <td>388.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>chr9</td>\n",
       "      <td>112340000</td>\n",
       "      <td>112370000</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>112335000.0</td>\n",
       "      <td>112375000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159525</th>\n",
       "      <td>chr15</td>\n",
       "      <td>49169871</td>\n",
       "      <td>49171029</td>\n",
       "      <td>1092.0</td>\n",
       "      <td>1257.0</td>\n",
       "      <td>1086.0</td>\n",
       "      <td>chr15</td>\n",
       "      <td>49130000</td>\n",
       "      <td>49170000</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>49125000.0</td>\n",
       "      <td>49175000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159526</th>\n",
       "      <td>chr3</td>\n",
       "      <td>185807568</td>\n",
       "      <td>185808472</td>\n",
       "      <td>1093.0</td>\n",
       "      <td>1255.0</td>\n",
       "      <td>743.0</td>\n",
       "      <td>chr3</td>\n",
       "      <td>185760000</td>\n",
       "      <td>185850000</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>185755000.0</td>\n",
       "      <td>185855000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159533</th>\n",
       "      <td>chr21</td>\n",
       "      <td>14382384</td>\n",
       "      <td>14384213</td>\n",
       "      <td>1110.0</td>\n",
       "      <td>1267.0</td>\n",
       "      <td>1212.0</td>\n",
       "      <td>chr21</td>\n",
       "      <td>14350000</td>\n",
       "      <td>14410000</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>14345000.0</td>\n",
       "      <td>14415000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159538</th>\n",
       "      <td>chr7</td>\n",
       "      <td>25861697</td>\n",
       "      <td>25863276</td>\n",
       "      <td>1117.0</td>\n",
       "      <td>1121.0</td>\n",
       "      <td>1024.0</td>\n",
       "      <td>chr7</td>\n",
       "      <td>25830000</td>\n",
       "      <td>25890000</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>25825000.0</td>\n",
       "      <td>25895000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159550</th>\n",
       "      <td>chr5</td>\n",
       "      <td>90557902</td>\n",
       "      <td>90559422</td>\n",
       "      <td>1133.0</td>\n",
       "      <td>1270.0</td>\n",
       "      <td>1179.0</td>\n",
       "      <td>chr5</td>\n",
       "      <td>90510000</td>\n",
       "      <td>90570000</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>90505000.0</td>\n",
       "      <td>90575000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15421 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        chrom      start        end  score_M  score_mG  score_pG chrom_  \\\n",
       "46      chr20   18279312   18279628      0.0      65.0       0.0  chr20   \n",
       "47      chr20   18272520   18272764      0.0     313.0       0.0  chr20   \n",
       "48      chr20   18263263   18264156      0.0    1084.0     314.0  chr20   \n",
       "81       chr9  112360232  112360692      0.0     237.0       0.0   chr9   \n",
       "91       chr9  112348341  112348979      0.0     388.0     175.0   chr9   \n",
       "...       ...        ...        ...      ...       ...       ...    ...   \n",
       "159525  chr15   49169871   49171029   1092.0    1257.0    1086.0  chr15   \n",
       "159526   chr3  185807568  185808472   1093.0    1255.0     743.0   chr3   \n",
       "159533  chr21   14382384   14384213   1110.0    1267.0    1212.0  chr21   \n",
       "159538   chr7   25861697   25863276   1117.0    1121.0    1024.0   chr7   \n",
       "159550   chr5   90557902   90559422   1133.0    1270.0    1179.0   chr5   \n",
       "\n",
       "           start_       end_  sizemaybe_   start_ext_     end_ext_  \n",
       "46       18260000   18290000     30000.0   18255000.0   18295000.0  \n",
       "47       18260000   18290000     30000.0   18255000.0   18295000.0  \n",
       "48       18260000   18290000     30000.0   18255000.0   18295000.0  \n",
       "81      112340000  112370000     30000.0  112335000.0  112375000.0  \n",
       "91      112340000  112370000     30000.0  112335000.0  112375000.0  \n",
       "...           ...        ...         ...          ...          ...  \n",
       "159525   49130000   49170000     40000.0   49125000.0   49175000.0  \n",
       "159526  185760000  185850000     90000.0  185755000.0  185855000.0  \n",
       "159533   14350000   14410000     60000.0   14345000.0   14415000.0  \n",
       "159538   25830000   25890000     60000.0   25825000.0   25895000.0  \n",
       "159550   90510000   90570000     60000.0   90505000.0   90575000.0  \n",
       "\n",
       "[15421 rows x 12 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "union_IDs_5=bf.overlap(union, g1_spec, how='left').drop_duplicates(subset=['chrom','start','end']).dropna()\n",
    "union_IDs_cyto=bf.overlap(union, cyt_g1,how='left').drop_duplicates(subset=['chrom','start','end']).dropna()\n",
    "union_IDs=bf.overlap(union, g1,how='left').drop_duplicates(subset=['chrom','start','end']).dropna()\n",
    "\n",
    "print(len(union_IDs_5),len(union_IDs_cyto))\n",
    "union_IDs\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "e36741be",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/allana.schooley-umw/miniconda3/envs/open2c2v2/lib/python3.9/site-packages/upsetplot/plotting.py:795: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
      "\n",
      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
      "\n",
      "\n",
      "  styles[\"linewidth\"].fillna(1, inplace=True)\n",
      "/home/allana.schooley-umw/miniconda3/envs/open2c2v2/lib/python3.9/site-packages/upsetplot/plotting.py:796: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
      "\n",
      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
      "\n",
      "\n",
      "  styles[\"facecolor\"].fillna(self._facecolor, inplace=True)\n",
      "/home/allana.schooley-umw/miniconda3/envs/open2c2v2/lib/python3.9/site-packages/upsetplot/plotting.py:797: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
      "\n",
      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
      "\n",
      "\n",
      "  styles[\"edgecolor\"].fillna(styles[\"facecolor\"], inplace=True)\n",
      "/home/allana.schooley-umw/miniconda3/envs/open2c2v2/lib/python3.9/site-packages/upsetplot/plotting.py:798: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
      "\n",
      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
      "\n",
      "\n",
      "  styles[\"linestyle\"].fillna(\"solid\", inplace=True)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'matrix': <AxesSubplot: >,\n",
       " 'shading': <AxesSubplot: >,\n",
       " 'totals': <AxesSubplot: >,\n",
       " 'intersections': <AxesSubplot: ylabel='Intersection size'>}"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 577.778x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import pandas as pd\n",
    "from upsetplot import plot, from_indicators\n",
    "from upsetplot import generate_counts, UpSet\n",
    "\n",
    "updata=union_IDs[['score_M','score_mG','score_pG']].copy()\n",
    "updata['pro-metaphase']=updata['score_M']\n",
    "updata['control G1']=updata['score_mG']\n",
    "updata['ΔRanGAP1 G1']=updata['score_pG']\n",
    "updata=updata[['pro-metaphase','control G1','ΔRanGAP1 G1']]\n",
    "updata.replace(0, np.nan, inplace=True)\n",
    "\n",
    "updata=from_indicators(indicators=pd.notna, data=updata)\n",
    "upset = UpSet(updata,sort_by='cardinality',show_percentages=True)\n",
    "upset.style_subsets(present=['pro-metaphase'], facecolor=\"darkgoldenrod\", label=None,edgecolor='black',linewidth=0.5)\n",
    "upset.style_subsets(present=['control G1'], absent=['pro-metaphase','ΔRanGAP1 G1'],facecolor=\"royalblue\", label=None,edgecolor='black',linewidth=0.5)\n",
    "upset.style_subsets(present=['ΔRanGAP1 G1'], absent=['pro-metaphase'],facecolor=\"firebrick\", label=None,edgecolor='black',linewidth=0.5)\n",
    "\n",
    "upset.plot(fig = plt.figure(figsize=(13, 13)))\n",
    "#plt.suptitle(\"ATAC peaks\")\n",
    "#plt.savefig('/atacpeaks_all_atID_upset_colours_new.pdf', bbox_inches = 'tight', dpi = 300)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60ffc255",
   "metadata": {},
   "source": [
    "# Coverage at peaks\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "bfc4ad1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>cov_cov</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>826630</td>\n",
       "      <td>828066</td>\n",
       "      <td>7350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>858687</td>\n",
       "      <td>859056</td>\n",
       "      <td>212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>866171</td>\n",
       "      <td>866515</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>869443</td>\n",
       "      <td>870290</td>\n",
       "      <td>3679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>875202</td>\n",
       "      <td>875737</td>\n",
       "      <td>321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159067</th>\n",
       "      <td>chrY</td>\n",
       "      <td>21845260</td>\n",
       "      <td>21846134</td>\n",
       "      <td>944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159068</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22263963</td>\n",
       "      <td>22264219</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159069</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22265642</td>\n",
       "      <td>22266678</td>\n",
       "      <td>2556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159070</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22370661</td>\n",
       "      <td>22371030</td>\n",
       "      <td>944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159071</th>\n",
       "      <td>chrY</td>\n",
       "      <td>26319533</td>\n",
       "      <td>26319755</td>\n",
       "      <td>198</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>159072 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom     start       end  cov_cov\n",
       "0       chr1    826630    828066     7350\n",
       "1       chr1    858687    859056      212\n",
       "2       chr1    866171    866515      177\n",
       "3       chr1    869443    870290     3679\n",
       "4       chr1    875202    875737      321\n",
       "...      ...       ...       ...      ...\n",
       "159067  chrY  21845260  21846134      944\n",
       "159068  chrY  22263963  22264219      116\n",
       "159069  chrY  22265642  22266678     2556\n",
       "159070  chrY  22370661  22371030      944\n",
       "159071  chrY  26319533  26319755      198\n",
       "\n",
       "[159072 rows x 4 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Mp=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/coverage/cov_allpeaks/Mp.out',sep='\\t')\n",
    "mGp=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/coverage/cov_allpeaks/mGp.out',sep='\\t')\n",
    "pGp=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/coverage/cov_allpeaks/pGp.out',sep='\\t')\n",
    "Mp\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "060dd3e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_Mp</th>\n",
       "      <th>score_mGp</th>\n",
       "      <th>score_pGp</th>\n",
       "      <th>count_Mp</th>\n",
       "      <th>count_mGp</th>\n",
       "      <th>count_pGp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>826630</td>\n",
       "      <td>828066</td>\n",
       "      <td>616.0</td>\n",
       "      <td>723.0</td>\n",
       "      <td>734.0</td>\n",
       "      <td>7350</td>\n",
       "      <td>3597</td>\n",
       "      <td>5620.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>858687</td>\n",
       "      <td>859056</td>\n",
       "      <td>0.0</td>\n",
       "      <td>201.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>212</td>\n",
       "      <td>239</td>\n",
       "      <td>73.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>866171</td>\n",
       "      <td>866515</td>\n",
       "      <td>0.0</td>\n",
       "      <td>274.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>177</td>\n",
       "      <td>240</td>\n",
       "      <td>61.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>869443</td>\n",
       "      <td>870290</td>\n",
       "      <td>598.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>3679</td>\n",
       "      <td>1629</td>\n",
       "      <td>1804.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>875202</td>\n",
       "      <td>875737</td>\n",
       "      <td>0.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>321</td>\n",
       "      <td>222</td>\n",
       "      <td>204.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159067</th>\n",
       "      <td>chrY</td>\n",
       "      <td>21845260</td>\n",
       "      <td>21846134</td>\n",
       "      <td>0.0</td>\n",
       "      <td>794.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>944</td>\n",
       "      <td>1363</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159068</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22263963</td>\n",
       "      <td>22264219</td>\n",
       "      <td>0.0</td>\n",
       "      <td>216.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>116</td>\n",
       "      <td>165</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159069</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22265642</td>\n",
       "      <td>22266678</td>\n",
       "      <td>769.0</td>\n",
       "      <td>1007.0</td>\n",
       "      <td>467.0</td>\n",
       "      <td>2556</td>\n",
       "      <td>2369</td>\n",
       "      <td>745.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159070</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22370661</td>\n",
       "      <td>22371030</td>\n",
       "      <td>479.0</td>\n",
       "      <td>734.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>944</td>\n",
       "      <td>1173</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159071</th>\n",
       "      <td>chrY</td>\n",
       "      <td>26319533</td>\n",
       "      <td>26319755</td>\n",
       "      <td>0.0</td>\n",
       "      <td>342.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>198</td>\n",
       "      <td>331</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>159072 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom     start       end  score_Mp  score_mGp  score_pGp  count_Mp  \\\n",
       "0       chr1    826630    828066     616.0      723.0      734.0      7350   \n",
       "1       chr1    858687    859056       0.0      201.0        0.0       212   \n",
       "2       chr1    866171    866515       0.0      274.0        0.0       177   \n",
       "3       chr1    869443    870290     598.0      558.0      642.0      3679   \n",
       "4       chr1    875202    875737       0.0       82.0        0.0       321   \n",
       "...      ...       ...       ...       ...        ...        ...       ...   \n",
       "159067  chrY  21845260  21846134       0.0      794.0      146.0       944   \n",
       "159068  chrY  22263963  22264219       0.0      216.0        0.0       116   \n",
       "159069  chrY  22265642  22266678     769.0     1007.0      467.0      2556   \n",
       "159070  chrY  22370661  22371030     479.0      734.0      153.0       944   \n",
       "159071  chrY  26319533  26319755       0.0      342.0        0.0       198   \n",
       "\n",
       "        count_mGp  count_pGp  \n",
       "0            3597     5620.0  \n",
       "1             239       73.0  \n",
       "2             240       61.0  \n",
       "3            1629     1804.0  \n",
       "4             222      204.0  \n",
       "...           ...        ...  \n",
       "159067       1363      193.0  \n",
       "159068        165       23.0  \n",
       "159069       2369      745.0  \n",
       "159070       1173      154.0  \n",
       "159071        331       45.0  \n",
       "\n",
       "[159072 rows x 9 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "union=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/union_R1R3_narrowPeaks_bothfirst_pmit.sorted',sep='\\t',\n",
    "                  names=['chrom','start','end','score_Mp','score_mGp','score_pGp'])\n",
    "#since the file were sorted and inputs were identical can simply add columns.  otherwise need to merge\n",
    "union['count_Mp']=Mp['cov_cov']\n",
    "union['count_mGp']=mGp['cov_cov']\n",
    "union['count_pGp']=pGp['cov_cov']\n",
    "union\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "0d1f0787-79fe-4cd9-9d0a-73d087cb45e2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0016218326255528711 0.0026477997869368466 0.0029600911307863962\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_Mp</th>\n",
       "      <th>score_mGp</th>\n",
       "      <th>score_pGp</th>\n",
       "      <th>count_Mp</th>\n",
       "      <th>count_mGp</th>\n",
       "      <th>count_pGp</th>\n",
       "      <th>count_Mp_norm</th>\n",
       "      <th>count_mGp_norm</th>\n",
       "      <th>count_pGp_norm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>826630</td>\n",
       "      <td>828066</td>\n",
       "      <td>616.0</td>\n",
       "      <td>723.0</td>\n",
       "      <td>734.0</td>\n",
       "      <td>7350</td>\n",
       "      <td>3597</td>\n",
       "      <td>5620.0</td>\n",
       "      <td>11.920470</td>\n",
       "      <td>9.524136</td>\n",
       "      <td>16.635712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>858687</td>\n",
       "      <td>859056</td>\n",
       "      <td>0.0</td>\n",
       "      <td>201.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>212</td>\n",
       "      <td>239</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.343829</td>\n",
       "      <td>0.632824</td>\n",
       "      <td>0.216087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>866171</td>\n",
       "      <td>866515</td>\n",
       "      <td>0.0</td>\n",
       "      <td>274.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>177</td>\n",
       "      <td>240</td>\n",
       "      <td>61.0</td>\n",
       "      <td>0.287064</td>\n",
       "      <td>0.635472</td>\n",
       "      <td>0.180566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>869443</td>\n",
       "      <td>870290</td>\n",
       "      <td>598.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>3679</td>\n",
       "      <td>1629</td>\n",
       "      <td>1804.0</td>\n",
       "      <td>5.966722</td>\n",
       "      <td>4.313266</td>\n",
       "      <td>5.340004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>875202</td>\n",
       "      <td>875737</td>\n",
       "      <td>0.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>321</td>\n",
       "      <td>222</td>\n",
       "      <td>204.0</td>\n",
       "      <td>0.520608</td>\n",
       "      <td>0.587812</td>\n",
       "      <td>0.603859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159067</th>\n",
       "      <td>chrY</td>\n",
       "      <td>21845260</td>\n",
       "      <td>21846134</td>\n",
       "      <td>0.0</td>\n",
       "      <td>794.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>944</td>\n",
       "      <td>1363</td>\n",
       "      <td>193.0</td>\n",
       "      <td>1.531010</td>\n",
       "      <td>3.608951</td>\n",
       "      <td>0.571298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159068</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22263963</td>\n",
       "      <td>22264219</td>\n",
       "      <td>0.0</td>\n",
       "      <td>216.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>116</td>\n",
       "      <td>165</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.188133</td>\n",
       "      <td>0.436887</td>\n",
       "      <td>0.068082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159069</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22265642</td>\n",
       "      <td>22266678</td>\n",
       "      <td>769.0</td>\n",
       "      <td>1007.0</td>\n",
       "      <td>467.0</td>\n",
       "      <td>2556</td>\n",
       "      <td>2369</td>\n",
       "      <td>745.0</td>\n",
       "      <td>4.145404</td>\n",
       "      <td>6.272638</td>\n",
       "      <td>2.205268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159070</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22370661</td>\n",
       "      <td>22371030</td>\n",
       "      <td>479.0</td>\n",
       "      <td>734.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>944</td>\n",
       "      <td>1173</td>\n",
       "      <td>154.0</td>\n",
       "      <td>1.531010</td>\n",
       "      <td>3.105869</td>\n",
       "      <td>0.455854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159071</th>\n",
       "      <td>chrY</td>\n",
       "      <td>26319533</td>\n",
       "      <td>26319755</td>\n",
       "      <td>0.0</td>\n",
       "      <td>342.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>198</td>\n",
       "      <td>331</td>\n",
       "      <td>45.0</td>\n",
       "      <td>0.321123</td>\n",
       "      <td>0.876422</td>\n",
       "      <td>0.133204</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>159072 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom     start       end  score_Mp  score_mGp  score_pGp  count_Mp  \\\n",
       "0       chr1    826630    828066     616.0      723.0      734.0      7350   \n",
       "1       chr1    858687    859056       0.0      201.0        0.0       212   \n",
       "2       chr1    866171    866515       0.0      274.0        0.0       177   \n",
       "3       chr1    869443    870290     598.0      558.0      642.0      3679   \n",
       "4       chr1    875202    875737       0.0       82.0        0.0       321   \n",
       "...      ...       ...       ...       ...        ...        ...       ...   \n",
       "159067  chrY  21845260  21846134       0.0      794.0      146.0       944   \n",
       "159068  chrY  22263963  22264219       0.0      216.0        0.0       116   \n",
       "159069  chrY  22265642  22266678     769.0     1007.0      467.0      2556   \n",
       "159070  chrY  22370661  22371030     479.0      734.0      153.0       944   \n",
       "159071  chrY  26319533  26319755       0.0      342.0        0.0       198   \n",
       "\n",
       "        count_mGp  count_pGp  count_Mp_norm  count_mGp_norm  count_pGp_norm  \n",
       "0            3597     5620.0      11.920470        9.524136       16.635712  \n",
       "1             239       73.0       0.343829        0.632824        0.216087  \n",
       "2             240       61.0       0.287064        0.635472        0.180566  \n",
       "3            1629     1804.0       5.966722        4.313266        5.340004  \n",
       "4             222      204.0       0.520608        0.587812        0.603859  \n",
       "...           ...        ...            ...             ...             ...  \n",
       "159067       1363      193.0       1.531010        3.608951        0.571298  \n",
       "159068        165       23.0       0.188133        0.436887        0.068082  \n",
       "159069       2369      745.0       4.145404        6.272638        2.205268  \n",
       "159070       1173      154.0       1.531010        3.105869        0.455854  \n",
       "159071        331       45.0       0.321123        0.876422        0.133204  \n",
       "\n",
       "[159072 rows x 12 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#norm should be total reads\n",
    "  # 377672060 mGp.reducedchroms.p4m5_ends.sorted.bed\n",
    "  # 616586437 Mp.reducedchroms.p4m5_ends.sorted.bed\n",
    "  # 337827437 pGp.reducedchroms.p4m5_ends.sorted.bed\n",
    "\n",
    "norm_M=1000000/616586437\n",
    "norm_mG=1000000/377672060\n",
    "norm_pG=1000000/337827437\n",
    "\n",
    "union['count_Mp_norm']=union['count_Mp']*norm_M\n",
    "union['count_mGp_norm']=union['count_mGp']*norm_mG\n",
    "union['count_pGp_norm']=union['count_pGp']*norm_pG\n",
    "\n",
    "print(norm_M,norm_mG,norm_pG)\n",
    "\n",
    "union\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7379fd15-04f9-4f8f-92ec-6bd56a1f47bb",
   "metadata": {},
   "source": [
    "# overlap IDs\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "1c396b3b-8b51-4b75-ba79-5f0d269973d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>sizemaybe</th>\n",
       "      <th>start_ext</th>\n",
       "      <th>end_ext</th>\n",
       "      <th>chrom_</th>\n",
       "      <th>start_</th>\n",
       "      <th>end_</th>\n",
       "      <th>sizemaybe_</th>\n",
       "      <th>start_ext_</th>\n",
       "      <th>end_ext_</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>6590000</td>\n",
       "      <td>6620000</td>\n",
       "      <td>30000</td>\n",
       "      <td>6585000</td>\n",
       "      <td>6625000</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>7760000</td>\n",
       "      <td>7790000</td>\n",
       "      <td>30000</td>\n",
       "      <td>7755000</td>\n",
       "      <td>7795000</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>chr1</td>\n",
       "      <td>8080000</td>\n",
       "      <td>8110000</td>\n",
       "      <td>30000</td>\n",
       "      <td>8075000</td>\n",
       "      <td>8115000</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>chr1</td>\n",
       "      <td>9130000</td>\n",
       "      <td>9160000</td>\n",
       "      <td>30000</td>\n",
       "      <td>9125000</td>\n",
       "      <td>9165000</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>chr1</td>\n",
       "      <td>19890000</td>\n",
       "      <td>19920000</td>\n",
       "      <td>30000</td>\n",
       "      <td>19885000</td>\n",
       "      <td>19925000</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2136</th>\n",
       "      <td>chr21</td>\n",
       "      <td>39610000</td>\n",
       "      <td>39650000</td>\n",
       "      <td>40000</td>\n",
       "      <td>39605000</td>\n",
       "      <td>39655000</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2138</th>\n",
       "      <td>chr22</td>\n",
       "      <td>28830000</td>\n",
       "      <td>28860000</td>\n",
       "      <td>30000</td>\n",
       "      <td>28825000</td>\n",
       "      <td>28865000</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2139</th>\n",
       "      <td>chr22</td>\n",
       "      <td>28890000</td>\n",
       "      <td>28920000</td>\n",
       "      <td>30000</td>\n",
       "      <td>28885000</td>\n",
       "      <td>28925000</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2147</th>\n",
       "      <td>chr22</td>\n",
       "      <td>40000000</td>\n",
       "      <td>40050000</td>\n",
       "      <td>50000</td>\n",
       "      <td>39995000</td>\n",
       "      <td>40055000</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2148</th>\n",
       "      <td>chr22</td>\n",
       "      <td>44690000</td>\n",
       "      <td>44740000</td>\n",
       "      <td>50000</td>\n",
       "      <td>44685000</td>\n",
       "      <td>44745000</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1390 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      chrom     start       end  sizemaybe  start_ext   end_ext chrom_  \\\n",
       "2      chr1   6590000   6620000      30000    6585000   6625000   None   \n",
       "3      chr1   7760000   7790000      30000    7755000   7795000   None   \n",
       "5      chr1   8080000   8110000      30000    8075000   8115000   None   \n",
       "6      chr1   9130000   9160000      30000    9125000   9165000   None   \n",
       "8      chr1  19890000  19920000      30000   19885000  19925000   None   \n",
       "...     ...       ...       ...        ...        ...       ...    ...   \n",
       "2136  chr21  39610000  39650000      40000   39605000  39655000   None   \n",
       "2138  chr22  28830000  28860000      30000   28825000  28865000   None   \n",
       "2139  chr22  28890000  28920000      30000   28885000  28925000   None   \n",
       "2147  chr22  40000000  40050000      50000   39995000  40055000   None   \n",
       "2148  chr22  44690000  44740000      50000   44685000  44745000   None   \n",
       "\n",
       "      start_  end_  sizemaybe_  start_ext_  end_ext_  \n",
       "2        NaN   NaN         NaN        <NA>      <NA>  \n",
       "3        NaN   NaN         NaN        <NA>      <NA>  \n",
       "5        NaN   NaN         NaN        <NA>      <NA>  \n",
       "6        NaN   NaN         NaN        <NA>      <NA>  \n",
       "8        NaN   NaN         NaN        <NA>      <NA>  \n",
       "...      ...   ...         ...         ...       ...  \n",
       "2136     NaN   NaN         NaN        <NA>      <NA>  \n",
       "2138     NaN   NaN         NaN        <NA>      <NA>  \n",
       "2139     NaN   NaN         NaN        <NA>      <NA>  \n",
       "2147     NaN   NaN         NaN        <NA>      <NA>  \n",
       "2148     NaN   NaN         NaN        <NA>      <NA>  \n",
       "\n",
       "[1390 rows x 12 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cyt=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/nativecomps/240708_enrich/pCyto_2X_enrichment.pixel_derived.signal_fullpeaks.bed',\n",
    "               sep='\\t',names=['chrom','start','end','sizemaybe'])\n",
    "cyt['start_ext']=cyt['start']-5000\n",
    "cyt['end_ext']=cyt['end']+5000\n",
    "g1=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/nativecomps/240708_enrich/5hr_2X_enrichment.pixel_derived.signal_fullpeaks.bed',\n",
    "               sep='\\t',names=['chrom','start','end','sizemaybe'])\n",
    "g1['start_ext']=g1['start']-5000\n",
    "g1['end_ext']=g1['end']+5000\n",
    "\n",
    "cyt_g1=bf.overlap(g1,cyt,cols1=['chrom','start_ext','end_ext'],cols2=['chrom','start_ext','end_ext']).drop_duplicates(['chrom','start_ext','end_ext']).dropna()\n",
    "g1_spec=bf.overlap(g1,cyt,cols1=['chrom','start_ext','end_ext'],cols2=['chrom','start_ext','end_ext'])\n",
    "g1_spec=g1_spec[g1_spec['start_'].isnull()].drop_duplicates(['chrom','start_ext','end_ext'])\n",
    "g1_spec\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "31c532bf-be5a-478e-b508-118909db724a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_Mp</th>\n",
       "      <th>score_mGp</th>\n",
       "      <th>score_pGp</th>\n",
       "      <th>count_Mp</th>\n",
       "      <th>count_mGp</th>\n",
       "      <th>count_pGp</th>\n",
       "      <th>count_Mp_norm</th>\n",
       "      <th>...</th>\n",
       "      <th>end_</th>\n",
       "      <th>sizemaybe_</th>\n",
       "      <th>start_ext_</th>\n",
       "      <th>end_ext_</th>\n",
       "      <th>chrom__</th>\n",
       "      <th>start__</th>\n",
       "      <th>end__</th>\n",
       "      <th>sizemaybe__</th>\n",
       "      <th>start_ext__</th>\n",
       "      <th>end_ext__</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1005040</td>\n",
       "      <td>1005664</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1807</td>\n",
       "      <td>1539</td>\n",
       "      <td>521.0</td>\n",
       "      <td>2.930652</td>\n",
       "      <td>...</td>\n",
       "      <td>1040000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>1005000</td>\n",
       "      <td>1045000</td>\n",
       "      <td>chr1</td>\n",
       "      <td>980000.0</td>\n",
       "      <td>1060000.0</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>975000</td>\n",
       "      <td>1065000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1005751</td>\n",
       "      <td>1007061</td>\n",
       "      <td>355.0</td>\n",
       "      <td>503.0</td>\n",
       "      <td>592.0</td>\n",
       "      <td>8854</td>\n",
       "      <td>7360</td>\n",
       "      <td>7190.0</td>\n",
       "      <td>14.359706</td>\n",
       "      <td>...</td>\n",
       "      <td>1040000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>1005000</td>\n",
       "      <td>1045000</td>\n",
       "      <td>chr1</td>\n",
       "      <td>980000.0</td>\n",
       "      <td>1060000.0</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>975000</td>\n",
       "      <td>1065000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1013202</td>\n",
       "      <td>1014702</td>\n",
       "      <td>353.0</td>\n",
       "      <td>364.0</td>\n",
       "      <td>503.0</td>\n",
       "      <td>17335</td>\n",
       "      <td>9399</td>\n",
       "      <td>7878.0</td>\n",
       "      <td>28.114469</td>\n",
       "      <td>...</td>\n",
       "      <td>1040000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>1005000</td>\n",
       "      <td>1045000</td>\n",
       "      <td>chr1</td>\n",
       "      <td>980000.0</td>\n",
       "      <td>1060000.0</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>975000</td>\n",
       "      <td>1065000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1014809</td>\n",
       "      <td>1015185</td>\n",
       "      <td>0.0</td>\n",
       "      <td>158.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>2693</td>\n",
       "      <td>1527</td>\n",
       "      <td>805.0</td>\n",
       "      <td>4.367595</td>\n",
       "      <td>...</td>\n",
       "      <td>1040000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>1005000</td>\n",
       "      <td>1045000</td>\n",
       "      <td>chr1</td>\n",
       "      <td>980000.0</td>\n",
       "      <td>1060000.0</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>975000</td>\n",
       "      <td>1065000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1019220</td>\n",
       "      <td>1021796</td>\n",
       "      <td>139.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>188.0</td>\n",
       "      <td>50483</td>\n",
       "      <td>14644</td>\n",
       "      <td>10768.0</td>\n",
       "      <td>81.874976</td>\n",
       "      <td>...</td>\n",
       "      <td>1040000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>1005000</td>\n",
       "      <td>1045000</td>\n",
       "      <td>chr1</td>\n",
       "      <td>980000.0</td>\n",
       "      <td>1060000.0</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>975000</td>\n",
       "      <td>1065000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155902</th>\n",
       "      <td>chr9</td>\n",
       "      <td>137577765</td>\n",
       "      <td>137579579</td>\n",
       "      <td>443.0</td>\n",
       "      <td>490.0</td>\n",
       "      <td>640.0</td>\n",
       "      <td>18454</td>\n",
       "      <td>12116</td>\n",
       "      <td>9076.0</td>\n",
       "      <td>29.929299</td>\n",
       "      <td>...</td>\n",
       "      <td>137610000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>137575000</td>\n",
       "      <td>137615000</td>\n",
       "      <td>chr9</td>\n",
       "      <td>137580000.0</td>\n",
       "      <td>137630000.0</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>137575000</td>\n",
       "      <td>137635000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155903</th>\n",
       "      <td>chr9</td>\n",
       "      <td>137589356</td>\n",
       "      <td>137591497</td>\n",
       "      <td>431.0</td>\n",
       "      <td>498.0</td>\n",
       "      <td>514.0</td>\n",
       "      <td>23265</td>\n",
       "      <td>11566</td>\n",
       "      <td>9678.0</td>\n",
       "      <td>37.731936</td>\n",
       "      <td>...</td>\n",
       "      <td>137610000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>137575000</td>\n",
       "      <td>137615000</td>\n",
       "      <td>chr9</td>\n",
       "      <td>137580000.0</td>\n",
       "      <td>137630000.0</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>137575000</td>\n",
       "      <td>137635000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155904</th>\n",
       "      <td>chr9</td>\n",
       "      <td>137604137</td>\n",
       "      <td>137607038</td>\n",
       "      <td>394.0</td>\n",
       "      <td>426.0</td>\n",
       "      <td>470.0</td>\n",
       "      <td>59329</td>\n",
       "      <td>18048</td>\n",
       "      <td>16234.0</td>\n",
       "      <td>96.221708</td>\n",
       "      <td>...</td>\n",
       "      <td>137610000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>137575000</td>\n",
       "      <td>137615000</td>\n",
       "      <td>chr9</td>\n",
       "      <td>137580000.0</td>\n",
       "      <td>137630000.0</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>137575000</td>\n",
       "      <td>137635000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155905</th>\n",
       "      <td>chr9</td>\n",
       "      <td>137610954</td>\n",
       "      <td>137611280</td>\n",
       "      <td>0.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2308</td>\n",
       "      <td>2685</td>\n",
       "      <td>643.0</td>\n",
       "      <td>3.743190</td>\n",
       "      <td>...</td>\n",
       "      <td>137610000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>137575000</td>\n",
       "      <td>137615000</td>\n",
       "      <td>chr9</td>\n",
       "      <td>137580000.0</td>\n",
       "      <td>137630000.0</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>137575000</td>\n",
       "      <td>137635000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155906</th>\n",
       "      <td>chr9</td>\n",
       "      <td>137611618</td>\n",
       "      <td>137613179</td>\n",
       "      <td>295.0</td>\n",
       "      <td>444.0</td>\n",
       "      <td>487.0</td>\n",
       "      <td>42759</td>\n",
       "      <td>31004</td>\n",
       "      <td>13187.0</td>\n",
       "      <td>69.347941</td>\n",
       "      <td>...</td>\n",
       "      <td>137610000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>137575000</td>\n",
       "      <td>137615000</td>\n",
       "      <td>chr9</td>\n",
       "      <td>137580000.0</td>\n",
       "      <td>137630000.0</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>137575000</td>\n",
       "      <td>137635000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8334 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom      start        end  score_Mp  score_mGp  score_pGp  count_Mp  \\\n",
       "27      chr1    1005040    1005664       0.0       92.0        0.0      1807   \n",
       "28      chr1    1005751    1007061     355.0      503.0      592.0      8854   \n",
       "29      chr1    1013202    1014702     353.0      364.0      503.0     17335   \n",
       "30      chr1    1014809    1015185       0.0      158.0      104.0      2693   \n",
       "31      chr1    1019220    1021796     139.0      175.0      188.0     50483   \n",
       "...      ...        ...        ...       ...        ...        ...       ...   \n",
       "155902  chr9  137577765  137579579     443.0      490.0      640.0     18454   \n",
       "155903  chr9  137589356  137591497     431.0      498.0      514.0     23265   \n",
       "155904  chr9  137604137  137607038     394.0      426.0      470.0     59329   \n",
       "155905  chr9  137610954  137611280       0.0      165.0        0.0      2308   \n",
       "155906  chr9  137611618  137613179     295.0      444.0      487.0     42759   \n",
       "\n",
       "        count_mGp  count_pGp  count_Mp_norm  ...         end_  sizemaybe_  \\\n",
       "27           1539      521.0       2.930652  ...    1040000.0     30000.0   \n",
       "28           7360     7190.0      14.359706  ...    1040000.0     30000.0   \n",
       "29           9399     7878.0      28.114469  ...    1040000.0     30000.0   \n",
       "30           1527      805.0       4.367595  ...    1040000.0     30000.0   \n",
       "31          14644    10768.0      81.874976  ...    1040000.0     30000.0   \n",
       "...           ...        ...            ...  ...          ...         ...   \n",
       "155902      12116     9076.0      29.929299  ...  137610000.0     30000.0   \n",
       "155903      11566     9678.0      37.731936  ...  137610000.0     30000.0   \n",
       "155904      18048    16234.0      96.221708  ...  137610000.0     30000.0   \n",
       "155905       2685      643.0       3.743190  ...  137610000.0     30000.0   \n",
       "155906      31004    13187.0      69.347941  ...  137610000.0     30000.0   \n",
       "\n",
       "       start_ext_   end_ext_  chrom__      start__        end__  sizemaybe__  \\\n",
       "27        1005000    1045000     chr1     980000.0    1060000.0      80000.0   \n",
       "28        1005000    1045000     chr1     980000.0    1060000.0      80000.0   \n",
       "29        1005000    1045000     chr1     980000.0    1060000.0      80000.0   \n",
       "30        1005000    1045000     chr1     980000.0    1060000.0      80000.0   \n",
       "31        1005000    1045000     chr1     980000.0    1060000.0      80000.0   \n",
       "...           ...        ...      ...          ...          ...          ...   \n",
       "155902  137575000  137615000     chr9  137580000.0  137630000.0      50000.0   \n",
       "155903  137575000  137615000     chr9  137580000.0  137630000.0      50000.0   \n",
       "155904  137575000  137615000     chr9  137580000.0  137630000.0      50000.0   \n",
       "155905  137575000  137615000     chr9  137580000.0  137630000.0      50000.0   \n",
       "155906  137575000  137615000     chr9  137580000.0  137630000.0      50000.0   \n",
       "\n",
       "       start_ext__  end_ext__  \n",
       "27          975000    1065000  \n",
       "28          975000    1065000  \n",
       "29          975000    1065000  \n",
       "30          975000    1065000  \n",
       "31          975000    1065000  \n",
       "...            ...        ...  \n",
       "155902   137575000  137635000  \n",
       "155903   137575000  137635000  \n",
       "155904   137575000  137635000  \n",
       "155905   137575000  137635000  \n",
       "155906   137575000  137635000  \n",
       "\n",
       "[8334 rows x 24 columns]"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uID5=bf.overlap(union,g1_spec,cols2=['chrom','start_ext','end_ext']).dropna(subset='start_ext_').drop_duplicates(['chrom','start','end'])\n",
    "uIDc=bf.overlap(union,cyt_g1,cols2=['chrom','start_ext','end_ext']).dropna(subset='start_ext_').drop_duplicates(['chrom','start','end'])\n",
    "uID=bf.overlap(union,g1,cols2=['chrom','start_ext','end_ext']).dropna(subset='start_ext_').drop_duplicates(['chrom','start','end'])\n",
    "uIDc\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f99f711",
   "metadata": {},
   "source": [
    "# plotting coverage\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "aad87d30-b38f-4b38-9770-90b9b4c0ebde",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "159072 142542 17336\n"
     ]
    }
   ],
   "source": [
    "#union3=union[(union['score_mGp']>0)&(union['score_Mp']>0)]\n",
    "union2=union[(union['score_mGp']>0)]\n",
    "union_forplot=union2[union2['count_pGp_norm']>0]\n",
    "print(len(union),len(union_forplot),len(uID))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "99b052cc-be95-4e62-8c86-43d8b2650c68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x600 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#u=union\n",
    "i=uID[(uID['score_mGp']>0)]\n",
    "u=union_forplot\n",
    "r=len(i)/len(u)\n",
    "\n",
    "#u=union\n",
    "\n",
    "fig, ((ax1, ax2),(ax3,ax4),(ax5, ax6)) = plt.subplots(3, 2,figsize=(5, 6),sharey=True,sharex=True)\n",
    "\n",
    "hb1 = ax1.hexbin(u['count_Mp_norm'],u['count_mGp_norm'],gridsize=100,cmap='cividis',edgecolors='face',bins='log',xscale='log',yscale='log',vmax=450,vmin=0.5)\n",
    "hb2 = ax3.hexbin(u['count_Mp_norm'],u['count_pGp_norm'],gridsize=100,cmap='cividis',edgecolors='face',bins='log',xscale='log',yscale='log',vmax=450,vmin=0.5)\n",
    "hb3 = ax5.hexbin(u['count_pGp_norm'],u['count_mGp_norm'],gridsize=100,cmap='cividis',edgecolors='face',bins='log',xscale='log',yscale='log',vmax=450,vmin=0.5)\n",
    "\n",
    "hb4 = ax2.hexbin(i['count_Mp_norm'],i['count_mGp_norm'],gridsize=100,cmap='cividis',edgecolors='face',bins='log',xscale='log',yscale='log',vmax=45,vmin=0.5)\n",
    "hb5 = ax4.hexbin(i['count_Mp_norm'],i['count_pGp_norm'],gridsize=100,cmap='cividis',edgecolors='face',bins='log',xscale='log',yscale='log',vmax=45,vmin=0.5)\n",
    "hb6 = ax6.hexbin(i['count_pGp_norm'],i['count_mGp_norm'],gridsize=100,cmap='cividis',edgecolors='face',bins='log',xscale='log',yscale='log',vmax=45,vmin=0.5)\n",
    "\n",
    "\n",
    "\n",
    "axmin = 0.01\n",
    "axmax = 300\n",
    "\n",
    "for ax in [ax1, ax2,ax3,ax4,ax5,ax6]:\n",
    "    # ax.set_xscale('log')\n",
    "    # ax.set_yscale('log')\n",
    "    ax.axis([axmin, axmax, axmin, axmax])\n",
    "    ax.plot([axmin, axmax],[axmin, axmax],color=\"k\",lw=0.5, ls=':')\n",
    "    ax.vlines([0.1,1,10,100],0,200,lw=0.5, ls=':',color='k')\n",
    "    ax.hlines([0.1,1,10,100],0,200,lw=0.5, ls=':',color='k')\n",
    "for ax in [ax1, ax3,ax5]:\n",
    "    cb = fig.colorbar(hb1, ax=ax)\n",
    "for ax in [ax2, ax4,ax6]:\n",
    "    cb = fig.colorbar(hb4, ax=ax)\n",
    "    \n",
    "#plt.savefig(f'/coverage_hex_jul24_G1.pdf', bbox_inches = 'tight', dpi = 300)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ae8ccde",
   "metadata": {},
   "source": [
    "# Deseq2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "ae47d93d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: >"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWcAAAEsCAYAAAAfJ3IiAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA3LklEQVR4nO3de1hU1f4/8PeeAUZAQATlooi3QSwQyRtiRzHNy/GSx3PUvCN4CZUOot+SNKU8ivlTsdRMUwE1MzVNvyc7ZRkqKmooeVc0TQ04GBLGpQFh//7w6+SWi26cGWYz79fzrOdh9l6zP2tbfGaxZq21BVEURRARkVlR1XYDiIioIiZnIiIzxORMRGSGmJyJiMwQkzMRkRliciYiMkNMzkREZojJmYjIDDE5ExGZISZnIiIzxORMRAQgLi4OnTp1goODAxo3bowhQ4bg8uXLkjqhoaEQBEFSgoKCJHV0Oh0iIyPh6uoKe3t7DB48GLdv35bdHiZnIiIABw8exLRp05Camor9+/fj/v376NOnDwoLCyX1+vXrh6ysLH3Zt2+f5HxUVBR2796Nbdu2ISUlBQUFBRg4cCDKyspktUfgxkdERBXduXMHjRs3xsGDB9G9e3cAD3rOv/32G7744otK35Ofn49GjRph8+bNGDFiBAAgMzMTXl5e2LdvH/r27fvU8dlzJqI6TafT4d69e5Ki0+me+L78/HwAQMOGDSXHk5OT0bhxY/j4+GDSpEnIycnRn0tLS0NpaSn69OmjP+bp6Qk/Pz8cPXpUVrutZNVWkC+t25g85ktJoSaPWZr9X5PHtGnewuQxU1q/ZvKYDesVmDxm0f16Jo8JALZWT05WhtbBp+GTK1XixUEHZdXv3eF7vPPOO5Jj8+fPR2xsbJXvEUUR0dHRePHFF+Hn56c/3r9/fwwbNgze3t64fv063n77bbz00ktIS0uDRqNBdnY2bGxs4OzsLLmem5sbsrOzZbW7ziZnIqqbBJW8P/hjYmIQHR0tOabRaKp9z/Tp03HmzBmkpKRIjj8cqgAAPz8/dOzYEd7e3vjyyy8xdOjQKq8niiIEQZDVbiZnIlIUQSUvyWk0micm40dFRkZi7969OHToEJo2bVptXQ8PD3h7eyMjIwMA4O7ujpKSEuTl5Ul6zzk5OQgODpbVbo45E5GiCIJKVnlaoihi+vTp2LVrFw4cOIAWLZ48fJebm4tbt27Bw8MDANChQwdYW1tj//79+jpZWVk4d+6c7OTMnjMRKYrKSm2U606bNg1bt27Fnj174ODgoB8jdnJygq2tLQoKChAbG4u///3v8PDwwI0bN/DWW2/B1dUVf/vb3/R1w8PDMXPmTLi4uKBhw4aYNWsW/P390bt3b1ntYXImIkVRyRzWeFpr1qwBAISEhEiOJyQkIDQ0FGq1GmfPnsWmTZvw22+/wcPDAz179sRnn30GBwcHff34+HhYWVlh+PDhKC4uRq9evZCYmAi1Wt6HCpMzESmKnKEKOZ605MPW1hZff/31E69Tr149rFy5EitXrnym9jA5E5GiyP1CUKmYnIlIUeROpVMqo97ljRs3IAgCrKys8Msvv0jOZWVlwcrKCoIg4MaNG/rj//znP9GhQwdoNBq0b9/emM0jIgUSVIKsolQm+Qjy9PTEpk2bJMeSkpLQpEmTCnVFUURYWJhksjcR0UMqQSWrKJWsloeEhCAyMhJRUVFwdnaGm5sb1q1bh8LCQkyYMAEODg5o1aoVvvrqK8n7xo8fj4SEBMmxxMREjB8/vkKMDz74ANOmTUPLli1rcDtEVNex51yFpKQkuLq64sSJE4iMjERERASGDRuG4OBgnDp1Cn379sXYsWNRVFSkf8/gwYORl5enXwqZkpKCu3fvYtCgQYa7EyKyCEzOVQgICMDcuXOh1WoRExMDW1tbuLq6YtKkSdBqtZg3bx5yc3Nx5swZ/Xusra0xZswYbNy4EQCwceNGjBkzBtbW1ga5icp2nSoVyw1ybSIyLyq1WlZRKtnJuV27dvqf1Wo1XFxc4O/vrz/m5uYGAJJt9AAgPDwcO3bsQHZ2Nnbs2IGwsLCatrmCuLg4ODk5Scr28rsGuz4RmQ+VSiWrKJXslj/e2xUEQXLs4c5L5eXSnqufnx98fX0xcuRItG3bVrIN37OKiYlBfn6+pAxX1Ww7QiIyb48/JupJRalMOs85LCwMU6dO1S+TNJTKdp2yVvC3tERUNSWPI8th0uQ8adIkDBs2DA0aNKiyztWrV1FQUIDs7GwUFxcjPT0dAPDcc8/BxsbGNA0lIrPF5GyMYFZWcHV1rbbOxIkTcfDgn086CAwMBABcv34dzZs3N2bziEgBlDx3WQ5ZyTk5ObnCsUdX9z306AYi1W0m0r59+wrnK4tBRPQQe85ERGaIyZmIyAwpeQaGHEzORKQoaiM9CcXcMDkTkaKw50xEZIY45kxEZIaM9QxBc8PkTESKwmENIiIzxGENIiIzpGLPWdleSgo1ecwD4xNNHrPXttdMHrM8L9fkMUvLTL9kt0w0/ZQtG9V9k8d8ELe0VuLWBHvORERmiMmZiMgMqdXc+IiIyOxwtgYRkRnisAYRkRmykNzM5ExEysKeMxGRGWJyJiIyQ5ayCMWoc1Ju3LgBQRBgZWWFX375RXIuKysLVlZWEARB/6ir3Nxc9OvXD56entBoNPDy8sL06dNx7949YzaTiBREUAmyilKZZMKgp6cnNm3aJDmWlJSEJk2aSBujUuGVV17B3r17ceXKFSQmJuLbb7/Fa6+ZfhUcEZknQZBXlEpWcg4JCUFkZCSioqLg7OwMNzc3rFu3DoWFhZgwYQIcHBzQqlUrfPXVV5L3jR8/HgkJCZJjiYmJGD9+vOSYs7MzIiIi0LFjR3h7e6NXr16YOnUqDh8+XMPbI6K6RqUSZBWlkt1zTkpKgqurK06cOIHIyEhERERg2LBhCA4OxqlTp9C3b1+MHTsWRUVF+vcMHjwYeXl5SElJAQCkpKTg7t27GDRoULWxMjMzsWvXLvTo0UNuM4mojlKrVLKKUslueUBAAObOnQutVouYmBjY2trC1dUVkyZNglarxbx585Cbm4szZ87o32NtbY0xY8Zg48aNAICNGzdizJgxsLa2rjTGyJEjYWdnhyZNmsDR0RHr16+vtk06nQ737t2TFF1p7WwgQ0TGJajklacVFxeHTp06wcHBAY0bN8aQIUNw+fJlSR1RFBEbGwtPT0/Y2toiJCQE58+fl9TR6XSIjIyEq6sr7O3tMXjwYNy+fVv2fcpOzu3atdP/rFar4eLiAn9/f/0xNzc3AEBOTo7kfeHh4dixYweys7OxY8cOhIWFVRkjPj4ep06dwhdffIFr164hOjq62jbFxcXByclJUv7f3mS5t0ZECiAIgqzytA4ePIhp06YhNTUV+/fvx/3799GnTx8UFhbq6yxZsgTLly/HqlWrcPLkSbi7u+Pll1/G77//rq8TFRWF3bt3Y9u2bUhJSUFBQQEGDhyIsrIyWfcpeyrd471dQRAkxx7+Y5SXl0vq+fn5wdfXFyNHjkTbtm3h5+eH9PT0SmO4u7vD3d0dvr6+cHFxwV/+8he8/fbb8PDwqLR+TExMhQRevvt9ubdGRApgrHHk//znP5LXCQkJaNy4MdLS0tC9e3eIoogVK1Zgzpw5GDp0KIAHw7xubm7YunUrpkyZgvz8fGzYsAGbN29G7969AQBbtmyBl5cXvv32W/Tt2/ep22PSAZmwsDAkJydX22t+nCiKAB78qVAVjUYDR0dHSdFYcwo3UV0kd7ZGpcOe1eSTh/Lz8wEADRs2BABcv34d2dnZ6NOnj76ORqNBjx49cPToUQBAWloaSktLJXU8PT3h5+enr/O0TJqcJ02ahDt37mDixImVnt+3bx8SEhJw7tw53LhxA/v27UNERAS6deuG5s2bm7KpRGSm5M5zrmzYMy4urtoYoigiOjoaL774Ivz8/AAA2dnZAP4cun3Izc1Nfy47Oxs2NjZwdnauss7TMmn30srKCq6urlWet7W1xccff4wZM2ZAp9PBy8sLQ4cOxezZs03YSiIyZ3JHNSob9tRoNNW+Z/r06Thz5ox+htmjHh/HFkXxiWPbT1PncbKSc3JycoVjD1f3Pd6Qyn5+XPv27SXne/bsKbvrT0SWRW6S02hsnpiMHxUZGYm9e/fi0KFDaNq0qf64u7s7gAe940e//8rJydH3pt3d3VFSUoK8vDxJ7zknJwfBwcGy2q3cSYBEZJFUKnnlaYmiiOnTp2PXrl04cOAAWrRoITnfokULuLu7Y//+/fpjJSUlOHjwoD7xdujQAdbW1pI6WVlZOHfunOzkzG/NiEhRVGrjzNaYNm0atm7dij179sDBwUE/Ruzk5ARbW1sIgoCoqCgsWrQIWq0WWq0WixYtgp2dHUaNGqWvGx4ejpkzZ8LFxQUNGzbErFmz4O/vr5+98bSYnIlIUYy1K92aNWsAPNim4lEJCQkIDQ0FALzxxhsoLi7G1KlTkZeXhy5duuCbb76Bg4ODvn58fDysrKwwfPhwFBcXo1evXkhMTIRaLe9p7kzORKQoxtrMqLrvx/6MLSA2NhaxsbFV1qlXrx5WrlyJlStXPlN7mJyJSFGUvNOcHEzORKQoSt5pTg4mZyJSFPaciYjMkIV0nJmciUhZlPzoKTnqbHIuzf6vyWP22mb6x2l99+pHJo/Za+tkk8d8ii/S64Si+za1ElcQlPMPzGENIiIzpLaQdc1MzkSkKAp+8pQsTM5EpCgc1iAiMkNyd6VTKiZnIlIUC5msweRMRMpiIR1nJmciUhYmZyIiM2QpszWMfpshISEQBAGLFy+ucO6vf/2rfgu+h3bt2oW+ffvC1dUVgiAgPT3d2E0kIgWR+/RtpTLJZ5CXlxcSEhIkxzIzM3HgwAHJs7gAoLCwEN26das0mRMRqVXyilI987BGSEiI/tHhW7ZsgVqtRkREBBYsWKCf8jJw4EBs374dR44cQbdu3QAAiYmJ6NOnD27evCm53tixYwFU/uBYIiIl94blMMjnSlJSEqysrHD8+HF88MEHiI+Px/r16/XnbWxsMHr0aEnvOTExEWFhYYYIT0QWRCXIK0plkOTs5eWF+Ph4tGnTBqNHj0ZkZCTi4+MldcLDw7F9+3YUFhbi0KFDyM/Px4ABAwwRHjqdDvfu3ZMU3f37Brk2EZkXjjnLEBQUJFm107VrV2RkZKCsrEx/rF27dtBqtdi5cyc2btyIsWPHwtra2hDhERcXBycnJ0lZ/t0PBrk2EZkXQRBlFaUy6VS6sLAwrF69GhcuXMCJEycMdt2YmBhER0dLjuk+estg1yci86HkoQo5DNJzTk1NrfBaq9VWeBT4qFGjcPbsWfj5+eG5554zRGgAgEajgaOjo6RorDiFm6guspRhDYNksFu3biE6OhpTpkzBqVOnsHLlSixbtqxCPWdnZ2RlZVU7nHH37l3cvHkTmZmZAIDLly8DANzd3eHu7m6I5hKRgik54cphkOQ8btw4FBcXo3PnzlCr1YiMjMTkyZU/LaNBgwbVXmvv3r2YMGGC/vWrr74KAJg/f75ksQoRWSaV7HFkZWZzgyRna2trrFixAmvWrKlwLjk5udr3Pr4CMDQ0FKGhoYZoFhHVQew5ExGZISWv+pODyZmIFEWAcqfHyfHMyflJwxZERIbEYQ0iIjNkKfOcmZyJSFGUvOpPDiZnIlIUDmsQEZkhFb8QJCIyP+w5ExGZIY45K5xN8xYmj1mel2vymL22Vr5M3pi+G7XO5DGF46+bPGaZaPoumrWq7MmVjEAt1E7cmlBbSHK2kLU2RFRXGHNXukOHDmHQoEHw9PSEIAj44osvJOdDQ0MhCIKkBAUFSerodDpERkbC1dUV9vb2GDx4MG7fvi37PpmciUhRjLnZfmFhIQICArBq1aoq6/Tr1w9ZWVn6sm/fPsn5qKgo7N69G9u2bUNKSgoKCgowcOBAycNHnkadHdYgorrJmLM1+vfvj/79+1dbR6PRVLl9cX5+PjZs2IDNmzejd+/eAB48+NrLywvffvst+vbt+9RtYc+ZiBRF7rBGpc8Y1elqHD85ORmNGzeGj48PJk2ahJycHP25tLQ0lJaWok+fPvpjnp6e8PPzw9GjR2XFYXImIkWRO6xR2TNG4+LiahS7f//++OSTT3DgwAEsW7YMJ0+exEsvvaRP9tnZ2bCxsYGzs7PkfW5ubsjOzpYVi8MaRKQocnelq+wZoxqNpkaxR4wYof/Zz88PHTt2hLe3N7788ksMHTq0yveJoih5CPbTYHImIkWRu/GRRqOpcTJ+Eg8PD3h7eyMjIwPAg8fplZSUIC8vT9J7zsnJQXBwsKxrc1iDiBRFgCirGFNubi5u3boFDw8PAECHDh1gbW2N/fv36+tkZWXh3Llz5pecQ0JCIAgCFi9eXOHcX//6VwiCIHk2YGxsLHx9fWFvbw9nZ2f07t0bx48fN3YziUghVEK5rCJHQUEB0tPT9Y/Pu379OtLT03Hz5k0UFBRg1qxZOHbsGG7cuIHk5GQMGjQIrq6u+Nvf/gYAcHJyQnh4OGbOnInvvvsOp0+fxpgxY+Dv76+fvfHU9ymrdg15eXkhISFBciwzMxMHDhzQf+I85OPjg1WrVuHs2bNISUlB8+bN0adPH9y5c8cUTSUiM2fMec4//PADAgMDERgYCACIjo5GYGAg5s2bB7VajbNnz+KVV16Bj48Pxo8fDx8fHxw7dgwODg76a8THx2PIkCEYPnw4unXrBjs7O/zv//4v1Gq1vPsURfGZ+v0hISHw8/MD8GA+n1qtRkREBBYsWABBEBASEoLnnnsO27dvx549e9CtWzcAwKJFi5CamoqbN29iyJAhVT5Z+969e3BycsK3336LXr16PXW7/tj1/rPcVo3UxvJtlaOTyWPWzvLtcyaP2dCuyOQxy8rl/QIbiq1VzaeW1dQLPi41et+JS/my6nf2Nf3viCEYpOeclJQEKysrHD9+HB988AHi4+Oxfv16/XkbGxuMHj1a0ntOTExEWFhYtdctKSnBunXr4OTkhICAAEM0lYgUzpg9Z3NikOTs5eWF+Ph4tGnTBqNHj0ZkZCTi4+MldcLDw7F9+3YUFhbi0KFDyM/Px4ABAyq93r///W/Ur18f9erVQ3x8PPbv3w9XV9cq41c6ybz0viFujYjMjDl9IWhMBknOQUFBkjl8Xbt2RUZGhmQtebt27aDVarFz505s3LgRY8eOhbW1daXX69mzJ9LT03H06FH069cPw4cPl6zCeVxlk8z/3679VdYnIuViz9kIwsLCsHr1auzcubPaIQ17e3u0bt0aQUFB2LBhA6ysrLBhw4Yq68fExCA/P19S/mfoy8a4BSKqZew5y5CamlrhtVarrfDt5KhRo3D27Fn4+fnhueeee+rri6JY7Vp4jUYDR0dHSdFYc30NUV1kKT1ng2SwW7duITo6GlOmTMGpU6ewcuVKLFu2rEI9Z2dnZGVlVTmcUVhYiIULF2Lw4MHw8PBAbm4uPvzwQ9y+fRvDhg0zRFOJSOGU3BuWwyDJedy4cSguLkbnzp2hVqsRGRmJyZMrf0JHgwYNqryOWq3GpUuXkJSUhF9//RUuLi7o1KkTDh8+jOeff94QTSUihVPLXFiiVAZJztbW1lixYgXWrFlT4VxycnK17324EgcA6tWrh127dhmiSURUR7HnTERkhpiciYjMEJPzU3rSsAURkSEpeQaGHOw5E5GisOdMRGSGmJyJiMwQkzMRkRliciYiMkMCuAhF0VJav2bymKVlpn8k47M9KqFmhOOvmzym2MXP5DHb74w0eczJP/zd5DEBQKU2/f+7ibE1e5+KyZmIyPxwWIOIyAwJInvORERmhz1nIiIzxJ4zEZEZYs+ZiMgMsedMRGSG2HMmIjJDQm1M7q8FJpt5/vnnn+Oll16Cs7Mz7Ozs0KZNG4SFheH06dP6OllZWRg1ahTatGkDlUqFqKgoUzWPiBRCJZbJKkplkuT85ptvYsSIEWjfvj327t2L8+fPY926dWjVqhXeeustfT2dTodGjRphzpw5CAgIMEXTiEhhBLFcVlEq2cMaISEh8Pf3h1qtRlJSEmxsbLBgwQKMHj0a06dPx86dO9G4cWOsWrUK/fv3R2pqKpYsWYL3338fr7/+57LfFi1aoEePHhAf+ROlefPmeP/99wEAGzduNMDtEVFdw2GNaiQlJcHV1RUnTpxAZGQkIiIiMGzYMAQHB+PUqVPo27cvxo4di6KiInz66aeoX78+pk6dWum1BEF4phsgIssioFxWUaoaJeeAgADMnTsXWq0WMTExsLW1haurKyZNmgStVot58+YhNzcXZ86cwZUrV9CyZUtYWf3ZSV++fDnq16+vL/n5+Qa7ISKq40RRXlGoGiXndu3a6X9Wq9VwcXGBv7+//pibmxsAICcnB0DF3nFYWBjS09Oxdu1aFBYWSoY2akKn0+HevXuSUlKie6ZrEpF5spQx5xolZ2tra8lrQRAkxx4m4/Lycmi1Wly7dg2lpaX68w0aNEDr1q3RpEmTmoSvIC4uDk5OTpKybcMSg1ybiMyLAFFWUSqjz9YYOXIkCgoK8OGHHxotRkxMDPLz8yXl1fA3jBaPiGqPpfScjb4IpWvXrpg5cyZmzpyJn3/+GUOHDoWXlxeysrKwYcMGCIIAlerPz4j09HQAQEFBAe7cuYP09HTY2NjgueeeqzKGRqOBRqORHLOx4bAGUZ2k4HFkOUyyQnDp0qXo3Lkz1qxZg40bN6KoqAhubm7o3r07jh07BkdHR33dwMBA/c9paWnYunUrvL29cePGDVM0lYjMnKpcuQtL5JCdnJOTkyscqyxxPv4l3/DhwzF8+PAnXv9ZvxwkojpOwUMVcpj+wWFERM/AmGPOhw4dwqBBg+Dp6QlBEPDFF19IzouiiNjYWHh6esLW1hYhISE4f/68pI5Op0NkZCRcXV1hb2+PwYMH4/bt27Lvk8mZiBTFmLM1CgsLERAQgFWrVlV6fsmSJVi+fDlWrVqFkydPwt3dHS+//DJ+//13fZ2oqCjs3r0b27ZtQ0pKCgoKCjBw4ECUlckbjuGudESkLEYc1ujfvz/69+9feVhRxIoVKzBnzhwMHToUwIPV0m5ubti6dSumTJmC/Px8bNiwAZs3b0bv3r0BAFu2bIGXlxe+/fZb9O3b96nbwp4zESmKIIqySmWL1HQ6+bO5rl+/juzsbPTp00d/TKPRoEePHjh69CiAB5MYSktLJXU8PT3h5+enr/O0mJyJSFnEclmlskVqcXFxssNmZ2cD+HMF9ENubm76c9nZ2bCxsYGzs3OVdZ4WhzWISFlkzuiKiYlBdHS05Njj6yLkeHw7ClEUn7iB29PUeRx7zkSkKHJna2g0Gjg6OkpKTZKzu7s7AFToAefk5Oh70+7u7igpKUFeXl6VdZ4WkzMRKYpQXiarGEqLFi3g7u6O/fv364+VlJTg4MGDCA4OBgB06NAB1tbWkjpZWVk4d+6cvs7T4rAGESmLEWdrFBQU4OrVq/rX169fR3p6Oho2bIhmzZohKioKixYtglarhVarxaJFi2BnZ4dRo0YBAJycnBAeHo6ZM2fCxcUFDRs2xKxZs+Dv76+fvfG06mxyblivwOQxy0S1yWPWhjLR9A9IaL8z0uQxv/vHSpPHdF463uQxAaC+g02txK0JYz4J5YcffkDPnj31rx+OVY8fPx6JiYl44403UFxcjKlTpyIvLw9dunTBN998AwcHB/174uPjYWVlheHDh6O4uBi9evVCYmIi1Gp5+UEQ6+h66VNXck0ek8nZeNpf3mzymLWRnL9Z+oPJYwK1k5wXhtXsS7miwztk1bf7y7AaxaltdbbnTER1VN3sT1bA5ExEymIhGx8xORORoljK07eZnIlIWdhzJiIyQ0zORETmR5C59aZSMTkTkbJYyJizyZZvf/7553jppZfg7OwMOzs7tGnTBmFhYTh9+rS+TkpKCrp16wYXFxfY2trC19cX8fHxpmoiESmBzF3plMokyfnNN9/EiBEj0L59e+zduxfnz5/HunXr0KpVK7z11lv6evb29pg+fToOHTqEixcvYu7cuZg7dy7WrVtnimYSkRKIoryiULKHNUJCQuDv7w+1Wo2kpCTY2NhgwYIFGD16NKZPn46dO3eicePGWLVqFfr374/U1FQsWbIE77//Pl5//XX9dVq0aIEePXpIHugaGBgoefp28+bNsWvXLhw+fBiTJ09+xlslojqhXLm9YTlq1HNOSkqCq6srTpw4gcjISERERGDYsGEIDg7GqVOn0LdvX4wdOxZFRUX49NNPUb9+fUydOrXSa1W3x+np06dx9OhR9OjRoybNJKK6iMMaVQsICMDcuXOh1WoRExMDW1tbuLq6YtKkSdBqtZg3bx5yc3Nx5swZXLlyBS1btoSV1Z+d9OXLl6N+/fr6kp+fL7l+06ZNodFo0LFjR0ybNg0TJ058trskorqDwxpVa9eunf5ntVoNFxcX+Pv764893FQ6JycHQMXecVhYGAYPHozjx49jzJgxeHzvpcOHD6OgoACpqamYPXs2WrdujZEjR1bZHp1OV+GZYCUlOtjY1PxpB0RkpjisUTVra2vJa0EQJMceJuPy8nJotVpcu3YNpaWl+vMNGjRA69at0aRJk0qv36JFC/j7+2PSpEmYMWMGYmNjq21PZc8IS1i7oia3RkTmzkJ6zkafrTFy5EgUFBTgww8/rNH7xf97em51YmJikJ+fLykTpkTVKB4RmTkLGXM2+iKUrl27YubMmZg5cyZ+/vlnDB06FF5eXsjKysKGDRsgCAJUqgefEatXr0azZs3g6+sL4MG856VLlyIysvqN1jUaTYVngtnYlFZRm4gUjSsEDWfp0qXo3Lkz1qxZg40bN6KoqAhubm7o3r07jh07BkdHRwAPhkFiYmJw/fp1WFlZoVWrVli8eDGmTJliimYSkRJYyJiz7OScnJxc4diNGzcqHHv8S77hw4dj+PDh1V47MjLyib1kIrJwCh5HloN7axCRsih4HFkOJmciUpZy9pyJiMyOyJ4zEZEZYs+ZiMgMsedMRGR+RE6lIyIyQ1yEQkRkhjjPmYjI/HBYQ+GK7tczeUwb1X2Txyy6b2PymNYq0/9ZOfmHv5s8pvPS8SaP2WdWR5PHBIBem8JqIeqbNXsbZ2sQEZkfznMmIjJH7DkTEZkh9pyJiMyPyJ4zEZEZ4mwNIiLzI3IRChGR+bGUYQ2jP+CViMigjPSA19jYWAiCICnu7u5/hhVFxMbGwtPTE7a2tggJCcH58+eNcYcATJicr169irCwMDRr1gwajQZNmjRBr1698Mknn+D+/T8XbyxcuBDBwcGws7NDgwYNTNU8IlIIsVyUVeR4/vnnkZWVpS9nz57Vn1uyZAmWL1+OVatW4eTJk3B3d8fLL7+M33//3dC3CMBEwxonTpxA79698fzzz2P16tXw9fVFQUEBLly4gI8++gh+fn4ICAgAAJSUlGDYsGHo2rUrNmzYYIrmEZGCGHP5tpWVlaS3rI8pilixYgXmzJmDoUOHAgCSkpLg5uaGrVu3GuUh1AZJziEhIfDz8wMAbNmyBWq1GhEREViwYAEAIDQ0FD4+Pjhy5AhUqj8764GBgRg9erTkYbDvvPMOACAxMdEQTSOiukZmb1in00Gn00mOaTQaaDSaCnUzMjLg6ekJjUaDLl26YNGiRWjZsiWuX7+O7Oxs9OnTR3KNHj164OjRo0ZJzgYb1khKSoKVlRWOHz+ODz74APHx8Vi/fj3S09Nx8eJFzJo1S5KYHyUIgqGaQUR1nCiWyypxcXFwcnKSlLi4uArX7dKlCzZt2oSvv/4aH3/8MbKzsxEcHIzc3FxkZ2cDANzc3CTvcXNz058zNIMNa3h5eSE+Ph6CIKBNmzY4e/Ys4uPjMX/+fABAmzZt9HVzcnLQsmVL/eslS5Zg6tSphmoKEdVhcseRY2JiEB0dLTlWWa+5f//++p/9/f3RtWtXtGrVCklJSQgKCgJQsSMpiqLROpcG6zkHBQVJGtm1a1dkZGToXz96zsXFBenp6UhPT0eDBg1QUlLyTLF1Oh3u3bsnKSUluie/kYiUp7xcVtFoNHB0dJSUypLz4+zt7eHv74+MjAz9OPTjveScnJwKvWlDMfpsjdatWwMALl26pD+mVqvRunVrtG7dGlZWz955r+zPli0fL33m6xKR+Sm/Xyar1JROp8PFixfh4eGBFi1awN3dHfv379efLykpwcGDBxEcHGyI26rAYMk5NTW1wmutVosXXngBvr6+WLp0KcqN9C1rTEwM8vPzJWXMpFlGiUVEtUsURVnlac2aNQsHDx7E9evXcfz4cfzjH//AvXv3MH78eAiCgKioKCxatAi7d+/GuXPnEBoaCjs7O4waNcoo92mwMedbt24hOjoaU6ZMwalTp7By5UosW7YMgiAgISEBL7/8Mrp164aYmBi0bdsWpaWlOHToEO7cuQO1Wq2/zs2bN3H37l3cvHkTZWVlSE9PB/CgB16/fv1KY1f2zauNTaGhbo2IzImROnm3b9/GyJEj8euvv6JRo0YICgpCamoqvL29AQBvvPEGiouLMXXqVOTl5aFLly745ptv4ODgYJT2GCw5jxs3DsXFxejcuTPUajUiIyMxefJkAA/Go9PS0rBo0SJMmzYN2dnZsLe3R0BAAOLj4xEW9udTGObNm4ekpCT968DAQADA999/j5CQEEM1l4gUyljLt7dt21bteUEQEBsbi9jYWKPEf5zBkrO1tTVWrFiBNWvWVHrex8fnqeYuJyYmco4zEVXJUvbW4MZHRKQofMArEZEZYs9ZhuTkZENchojoidhzJiIyQ+w5ExGZIxlzl5WMyZmIFOVZVv0pCZMzESkKx5yJiMwQx5yJiMwQk7PC2VqZfstQG1WpyWMKgun/R1ULph/zU6lN/yzi+g42Jo/Za1PYkysZwXfjNpo85oCRb9bofRzWICIyQ+w5ExGZofIyJmciIrPDYQ0iIjPEYQ0iIjNUfp89ZyIis8NhDSIiM8RhDSIiM2QpszVMNrP/6tWrCAsLQ7NmzaDRaNCkSRP06tULn3zyCe7fv6+vN3jwYDRr1gz16tWDh4cHxo4di8zMTFM1k4jMnFguyipKZZLkfOLECbzwwgu4ePEiVq9ejXPnzuHf//43wsLC8NFHH+H8+fP6uj179sT27dtx+fJlfP7557h27Rr+8Y9/mKKZRKQAYnm5rKJUBhnWCAkJgZ+fHwBgy5YtUKvViIiIwIIFCwAAoaGh8PHxwZEjR6BS/fl5EBgYiNGjR0N8ZH/WGTNm6H/29vbG7NmzMWTIEJSWlsLa2toQzSUiBVNyb1gOg405JyUlITw8HMePH8cPP/yAyZMnw9vbGx07dsTFixfx6aefShLzowRBqPT43bt38cknnyA4OJiJmYgAcMxZNi8vL8THx6NNmzYYPXo0IiMjER8fjytXrgAA2rRpo6+bk5OD+vXr68uHH34oudabb74Je3t7uLi44ObNm9izZ0+1sXU6He7duycpJSWm3/iIiIyPY84yBQUFSXrAXbt2RUZGhv71o+dcXFyQnp6O9PR0NGjQACUlJZJr/c///A9Onz6Nb775Bmq1GuPGjZMMfTwuLi4OTk5OkpKwdoWhbo2IzEh5aZmsolRGn0rXunVrAMClS5fQvn17AIBardYft7Kq2ARXV1e4urrCx8cHbdu2hZeXF1JTU9G1a9dKY8TExCA6Olpy7PzNQgPeBRGZCw5ryJSamlrhtVarxQsvvABfX18sXboU5TX45vRhj1mnq3qYQqPRwNHRUVJsbDSyYxGR+bOUYQ2D9Zxv3bqF6OhoTJkyBadOncLKlSuxbNkyCIKAhIQEvPzyy+jWrRtiYmLQtm1blJaW4tChQ7hz5w7UajWAB1PuTpw4gRdffBHOzs746aefMG/ePLRq1arKXjMRWRZL6TkbLDmPGzcOxcXF6Ny5M9RqNSIjIzF58mQAD8aj09LSsGjRIkybNg3Z2dmwt7dHQEAA4uPjERb24OkPtra22LVrF+bPn4/CwkJ4eHigX79+2LZtGzQa9oSJCBDLlDt3WQ6DJWdra2usWLECa9asqfS8j48PEhMTq72Gv78/Dhw4YKgmEVEdpOShCjm4twYRKQqHNYiIzJDI5Pz0kpOTDXEZIqInKr/P5ExEZHbKivmFIBGR2RFLLaPnbLL9nImIDKH8viiryPXhhx+iRYsWqFevHjp06IDDhw8b4S6ejMmZiBRFLC2XVeT47LPPEBUVhTlz5uD06dP4y1/+gv79++PmzZtGupuqMTkTkaIYs+e8fPlyhIeHY+LEiWjbti1WrFgBLy+vKtdvGBPHnIlIUeSOOet0ugp782g0mgqrjktKSpCWlobZs2dLjvfp0wdHjx6tWWOfhUgSf/zxhzh//nzxjz/+YEzGZEwzi1kT8+fPFwFIyvz58yvU++WXX0QA4pEjRyTHFy5cKPr4+JiotX8SRLGajZIt0L179+Dk5IT8/Hw4OjoyJmMyphnFrImn7TlnZmaiSZMmOHr0qGSjtYULF2Lz5s24dOmSSdr7EIc1iKhOqywRV8bV1RVqtRrZ2dmS4zk5OXBzczNW86rELwSJiADY2NigQ4cO2L9/v+T4/v37ERwcbPL2sOdMRPR/oqOjMXbsWHTs2BFdu3bFunXrcPPmTbz22msmbwuT82M0Gg3mz59v0v2jGZMxGdM8jBgxArm5uXj33XeRlZUFPz8/7Nu3D97e3iZvC78QJCIyQxxzJiIyQ0zORERmiMmZiMgMMTkTEZkhJmciIjPE5ExEZIaYnImIzBCTczXu379vsk22//vf/9bKht4PY7/77rsGv25ubi6+//573L17FwDw66+/4r333sO7776LixcvGjzek1y8eBEtW7Y0+HXXr1+P8ePHIyEhAcCDDdvbtm2Lli1bYv78+QaP9ySFhYU4dOiQUa5dVlYmeX38+HEcOnQIpaWlRoln0Uy+D56CpKeniyqVyqDXvHfvnjh69GixWbNm4rhx40SdTidOnTpVFARBVKlUYvfu3cX8/HyDxnwSY9zn8ePHRScnJ1EQBNHZ2Vn84YcfxBYtWoharVZs3bq1aGtrK6alpRk05pMY4z7j4+NFe3t7cejQoaKHh4f4r3/9S3RxcRH/9a9/ie+++67o5OQkrl271qAxn8QY95mZmSl269ZNVKvVYvfu3cW7d++KAwYMEAVBEAVBEH18fMTMzEyDxrR0XL5tYm+99RbS0tIwa9Ys7Nq1C8OHD8e1a9dw+PBhlJeXY+rUqXjvvfewcOFCg8U8c+ZMtecvX75ssFgPzZkzB8OGDcPy5cuxdu1aDBkyBP369cPHH38MAJg4cSIWLFiA3bt3GyxmdHR0tefv3LljsFgPrV27FuvWrcOoUaNw+vRpdO7cGR999BHCw8MBAE2bNsXq1asxefJkg8c2pTfffBOiKGL37t345JNPMHDgQKjVaty6dQvl5eUYPXo0Fi5ciFWrVtV2U+sMi16+/cILL1R7vri4GFeuXKnwp9yzaNasGZKSktCzZ09kZmaiadOm2LNnDwYNGgQA2LdvH6Kjow26d6xKpYIgCKjsP/XD44IgGPQ+GzZsiCNHjqBt27YoLS1FvXr1cOzYMXTu3BkAcPr0aQwaNAi3b982WEy1Wo327dtXubdwQUEBTp06ZdD7tLOzw6VLl9CsWTMAQL169ZCWlobnn38eAHD16lV06tQJeXl5BovZsGHDas+XlZWhoKDAoPfp6emJXbt2ISgoCHfv3oWrqyv279+PXr16AQC+//57TJw4EdeuXTNYTEtn0T3nCxcu4NVXX0WLFi0qPZ+VlYUrV64YNGZOTg5at24N4MH/8La2tmjTpo3+/PPPP49bt24ZNKaLiwvee+89/S/S486fP6//cDCUkpIS2NraAgCsra1hZ2cHV1dXSZtyc3MNGlOr1WLGjBkYM2ZMpefT09PRoUMHg8a0s7NDYWGh/nWjRo1Qv359SZ379+8bNKZOp0NERAT8/f0rPf/zzz/jnXfeMWjMvLw8NGnSBMCDDwc7OzvJZkCtWrVCVlaWQWNaOotOzn5+fujSpQsiIiIqPZ+enq7/M9xQXFxccOfOHXh5eQEAXnnlFTRo0EB/vqCgwOC7fHXo0AGZmZlV7qz122+/VdqrfhZeXl746aef0Lx5cwDAtm3b4OHhoT+flZUlSdaG0KFDB6SlpVWZnKv66+FZ+Pr64syZM2jbti0AVPhgvXTpkv7fwFDat28PLy8vjB8/vtLzP/74o8GTc+PGjZGVlaX//3b69OmSHnxeXh7s7e0NGtPSWXRyfvHFF6sdb3VwcED37t0NGrNdu3Y4efKkfkhl69atkvMnT57U/6IbypQpUyS9u8c1a9ZMP9PAUF599VXk5OToXw8YMEByfu/evfohDkNZtmxZhccRPSogIADl5eUGjfnee+9Vm5Ru3ryJKVOmGDTmgAED8Ntvv1V5vmHDhhg3bpxBY7Zv314yLLV48WLJ+ZSUFLRr186gMS2dRY8514a7d+9CpVJJesuP+uqrr2Bra4uQkBCTtsvUioqKoFar69RewJbs5MmTsLW1hZ+fX203pc5gcqY66/fff5cMY6hUqgrjwXUhJtVNFp2cn3bRx8Nv4pUa82kXmMybN0/RMdPT0zFnzhx8+eWXAB4MSxUVFenPC4KAY8eOoVOnToqOWV5ejvPnz+u/EPzoo49QUlKiP69WqxEREQGVynBrzMrKynDhwgWTxrR0Fp2c1Wq1/ueH/wyCIEiOGXqKWW3EVKlU8PT0ROPGjav8QkwQBJw6dUrRMcPDw9G6dWvExMQAeJAo165diyZNmkAURWzcuBGiKGLz5s2Kjrl161asXbsWBw8e1Mds0KABrKwefIX066+/YsWKFfq51kqNaeks+gtBQRDQtGlThIaGYtCgQfr/0epazH79+uH7779Hx44dERYWhgEDBkg+JOpKzCNHjiA0NFRyLCgoSL9k29bWFsOHD1d8zISEhAoPHD148KA+5kcffYQtW7YYNFHWRkyLZ6KViGYpKytLXLx4sejr6yu6ubmJM2fOFC9cuFDnYorig+W3ixYtEn18fER3d3fxjTfeEC9dulSnYtrZ2Yk3btzQv16+fLlkKfzPP/8sajQaxcds0qSJmJ6ern9dv3598dq1a/rXFy5cEJ2dnRUf09JZdHJ+1OHDh8WwsDDRwcFB7NKli7hu3TqxrKyszsUURVE8ePCgGBoaKjo4OIjBwcFiUVFRnYjp7OwspqSkVHk+JSXF4AmkNmJqNBrx6tWr+tc5OTmS/28yMjJEGxsbxce0dBy9/z8vvvgiNmzYgIyMDNjZ2eG1116rdi6pUmMCQKdOndCzZ0+0bdsWp0+fNsmOYqaIGRgYiC+++KLK87t27UJgYKDiY7q5uUnm5zdq1EjyRdzFixfh7u6u+JgWr7Y/HczFkSNHxPDwcNHR0VHs1KmTuGbNGqP3Yk0d8+jRo+LEiRNFR0dHsWPHjuLq1avFvLw8o8UzdcydO3eKVlZW4qpVqyT/jvfv3xc/+OAD0draWtyxY4fiY06YMEEMDg6u9Fx5ebnYtWtXccKECYqPaeksOjlnZmaKixcvFtu0aSM2btxYnDFjhnju3Lk6F/O9994TfX19xUaNGolRUVHimTNnjBqvtmKKoii+8cYboiAIoqOjo9i+fXsxMDBQdHR0FAVBEGfNmlUnYl69elV0dHQUO3fuLG7fvl1MT08Xf/zxR/Gzzz4TO3XqJDo6OooZGRmKj2npLHoqnY2NDTw9PTF+/HgMHjwY1tbWldYz5LLU2oipUqnQrFkzDBw4EDY2NlXWW758uaJjPpSamopPP/0UGRkZAB5siDRy5EgEBQUZPFZtxTxx4gRCQ0Nx6dIlyZ4hvr6+SEhIQJcuXepETEtm0cn50TGzh3ONH//nMMacY1PHDAkJkcylrowgCDhw4ICiYz7qjz/+wJkzZ5CTk1NhP43BgwfXmZjp6en6nRO1Wq3Bx7fNJaYlsuh5ztevX7eImMnJyRWOiZUsgFF6zIf+85//YNy4ccjNzTX6B19txgSAtLQ0xMfHS3rsUVFRmDhxolHi1VZMS2TRszW8vb31xc3NDf/9739x9uxZ/Pjjj/rypKeIKCHmozZs2AA/Pz/Uq1cP9erVg5+fH9avX2+0eLURc/r06Rg2bBgyMzNRXl4uKcZKkrUR8+2338Y///lPDBo0CDt27MCOHTswaNAgzJgxA3Pnzq0zMS1W7Qx1m5evvvpKbNSokf55aI8WQz+LrTZjzp07V7S3txdnz54t7tmzR9yzZ484e/ZssX79+uKcOXPqTEwHBwfJnFxTqI2YLi4u4tatWysc37p1q+ji4lJnYloqJmdRFFu1aiVOnTpVzM7OrtMxLeWXecKECeL69euNcm1zitmgQQPxypUrFY5fvnxZdHJyqjMxLZVFfyH4kKOjI06fPo1WrVrV6ZjOzs44ceIEtFqt5PiVK1fQuXNnoyyAqY2YRUVFGDZsGBo1agR/f/8KM2Jef/31OhEzMjIS1tbWFWa8zJo1C8XFxVi9enWdiGmpmJwBhIWFoVu3bibdtKU2YlrKL/P69evx2muvwdbWFi4uLpIvIAVBwE8//VQnYkZGRmLTpk3w8vLST9lLTU3FrVu3MG7cOMkHhKGmLNZGTEvF5AzL6mlZwi+zu7s7Xn/9dcyePdtk+wvXRsyePXs+VT1DTlmsjZiWiskZltPTspRf5oYNG+LkyZMmHTKqjZhUtzE5w3J6WpZixowZaNSoEd566606HZPqNotehPJQSUkJRowYYdIkWRsxLUVZWRmWLFmCr7/+Gu3ataswZGSMsdDaiEl1G3vOYE+rrqluKMVYY6G1EZPqNiZnPPjybdOmTQgICDBZr6c2YhKRcjA5gz0tIjI/TM5ERGaI30YREZkhJmciIjPE5ExEZIaYnImIzBCTMxGRGWJyJiIyQ0zORERm6P8DUVb6wEleWYQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 375x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "de=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/unionmat_deseq2_vstT.txt',sep='\\t')\n",
    "\n",
    "fig, ax1 = plt.subplots(1, 1,figsize=(3.75, 3))\n",
    "\n",
    "sns.heatmap(de,cmap=\"coolwarm_r\",ax=ax1,vmin=0, vmax=250)\n",
    "\n",
    "#plt.savefig(f'/deseq2.pdf', bbox_inches = 'tight', dpi = 300)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa0ea706-258b-49d3-b08a-1e0009752e3c",
   "metadata": {},
   "source": [
    "# cCREs at ATAC peaks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "3468d8e3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "159072 142543 46447\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chrY</td>\n",
       "      <td>26319533</td>\n",
       "      <td>26319755</td>\n",
       "      <td>0.0</td>\n",
       "      <td>342.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18090847</td>\n",
       "      <td>18091143</td>\n",
       "      <td>0.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18090171</td>\n",
       "      <td>18090345</td>\n",
       "      <td>0.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18077179</td>\n",
       "      <td>18077421</td>\n",
       "      <td>0.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18074675</td>\n",
       "      <td>18075141</td>\n",
       "      <td>0.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159067</th>\n",
       "      <td>chr16</td>\n",
       "      <td>22436440</td>\n",
       "      <td>22437926</td>\n",
       "      <td>1211.0</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>1108.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159068</th>\n",
       "      <td>chr16</td>\n",
       "      <td>15153921</td>\n",
       "      <td>15155441</td>\n",
       "      <td>1234.0</td>\n",
       "      <td>960.0</td>\n",
       "      <td>1064.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159069</th>\n",
       "      <td>chr15</td>\n",
       "      <td>90497848</td>\n",
       "      <td>90498397</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>1404.0</td>\n",
       "      <td>654.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159070</th>\n",
       "      <td>chr9</td>\n",
       "      <td>96883802</td>\n",
       "      <td>96884970</td>\n",
       "      <td>1254.0</td>\n",
       "      <td>1433.0</td>\n",
       "      <td>1168.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159071</th>\n",
       "      <td>chr1</td>\n",
       "      <td>206202844</td>\n",
       "      <td>206203880</td>\n",
       "      <td>1373.0</td>\n",
       "      <td>1373.0</td>\n",
       "      <td>1302.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>159072 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        chrom      start        end  score_M  score_mG  score_pG\n",
       "0        chrY   26319533   26319755      0.0     342.0       0.0\n",
       "1       chr20   18090847   18091143      0.0      61.0       0.0\n",
       "2       chr20   18090171   18090345      0.0      77.0       0.0\n",
       "3       chr20   18077179   18077421      0.0      64.0       0.0\n",
       "4       chr20   18074675   18075141      0.0     112.0       0.0\n",
       "...       ...        ...        ...      ...       ...       ...\n",
       "159067  chr16   22436440   22437926   1211.0    1003.0    1108.0\n",
       "159068  chr16   15153921   15155441   1234.0     960.0    1064.0\n",
       "159069  chr15   90497848   90498397   1250.0    1404.0     654.0\n",
       "159070   chr9   96883802   96884970   1254.0    1433.0    1168.0\n",
       "159071   chr1  206202844  206203880   1373.0    1373.0    1302.0\n",
       "\n",
       "[159072 rows x 6 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "union=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/atac/nfatac_wbl_R1R3/result/filtered/macs3peaks/union_R1R3_narrowPeaks_bothfirst_pmit',\n",
    "                  sep='\\t',names=['chrom','start','end','score_M','score_mG','score_pG'])\n",
    "\n",
    "uniong1=union[union['score_mG']>0]\n",
    "uniong2=uniong1[(uniong1['score_pG']>0)&(uniong1['score_M']>0)]\n",
    "print(len(union),len(uniong1),len(uniong2))\n",
    "union\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "72699b8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>label</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>...</th>\n",
       "      <th>Z_ctcf</th>\n",
       "      <th>chrom_</th>\n",
       "      <th>start_</th>\n",
       "      <th>end_</th>\n",
       "      <th>label_</th>\n",
       "      <th>score_</th>\n",
       "      <th>strand_</th>\n",
       "      <th>name_</th>\n",
       "      <th>distance</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>827342</td>\n",
       "      <td>827691</td>\n",
       "      <td>EH38D2115342</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.175482</td>\n",
       "      <td>chr1</td>\n",
       "      <td>827522</td>\n",
       "      <td>827522</td>\n",
       "      <td>ENST00000473798.1</td>\n",
       "      <td>.</td>\n",
       "      <td>-</td>\n",
       "      <td>ENSG00000225880.5</td>\n",
       "      <td>0</td>\n",
       "      <td>pls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>904594</td>\n",
       "      <td>904931</td>\n",
       "      <td>EH38D2115410</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.881979</td>\n",
       "      <td>chr1</td>\n",
       "      <td>904834</td>\n",
       "      <td>904834</td>\n",
       "      <td>ENST00000607769.1</td>\n",
       "      <td>.</td>\n",
       "      <td>+</td>\n",
       "      <td>ENSG00000272438.1</td>\n",
       "      <td>0</td>\n",
       "      <td>pls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>959147</td>\n",
       "      <td>959495</td>\n",
       "      <td>EH38D2115511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.822329</td>\n",
       "      <td>chr1</td>\n",
       "      <td>959290</td>\n",
       "      <td>959290</td>\n",
       "      <td>ENST00000327044.6</td>\n",
       "      <td>.</td>\n",
       "      <td>-</td>\n",
       "      <td>ENSG00000188976.10</td>\n",
       "      <td>0</td>\n",
       "      <td>pls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>960392</td>\n",
       "      <td>960733</td>\n",
       "      <td>EH38D2115515</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-10.000000</td>\n",
       "      <td>chr1</td>\n",
       "      <td>960587</td>\n",
       "      <td>960587</td>\n",
       "      <td>ENST00000338591.7</td>\n",
       "      <td>.</td>\n",
       "      <td>+</td>\n",
       "      <td>ENSG00000187961.13</td>\n",
       "      <td>0</td>\n",
       "      <td>pls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>966292</td>\n",
       "      <td>966617</td>\n",
       "      <td>EH38D2115523</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.973521</td>\n",
       "      <td>chr1</td>\n",
       "      <td>966497</td>\n",
       "      <td>966497</td>\n",
       "      <td>ENST00000379410.7</td>\n",
       "      <td>.</td>\n",
       "      <td>+</td>\n",
       "      <td>ENSG00000187583.10</td>\n",
       "      <td>0</td>\n",
       "      <td>pls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165062</th>\n",
       "      <td>chrY</td>\n",
       "      <td>21602623</td>\n",
       "      <td>21602968</td>\n",
       "      <td>EH38D4327289</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.656758</td>\n",
       "      <td>chrY</td>\n",
       "      <td>21594666</td>\n",
       "      <td>21594666</td>\n",
       "      <td>ENST00000330337.2</td>\n",
       "      <td>.</td>\n",
       "      <td>-</td>\n",
       "      <td>ENSG00000184991.2</td>\n",
       "      <td>7957</td>\n",
       "      <td>justopen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165063</th>\n",
       "      <td>chrY</td>\n",
       "      <td>21840091</td>\n",
       "      <td>21840414</td>\n",
       "      <td>EH38D4327334</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-10.000000</td>\n",
       "      <td>chrY</td>\n",
       "      <td>21818218</td>\n",
       "      <td>21818218</td>\n",
       "      <td>ENST00000620993.1</td>\n",
       "      <td>.</td>\n",
       "      <td>-</td>\n",
       "      <td>ENSG00000277519.1</td>\n",
       "      <td>21873</td>\n",
       "      <td>justopen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165064</th>\n",
       "      <td>chrY</td>\n",
       "      <td>21845516</td>\n",
       "      <td>21845839</td>\n",
       "      <td>EH38D4327337</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-10.000000</td>\n",
       "      <td>chrY</td>\n",
       "      <td>21871331</td>\n",
       "      <td>21871331</td>\n",
       "      <td>ENST00000414540.1</td>\n",
       "      <td>.</td>\n",
       "      <td>+</td>\n",
       "      <td>ENSG00000229725.1</td>\n",
       "      <td>25492</td>\n",
       "      <td>justopen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165065</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22370653</td>\n",
       "      <td>22371001</td>\n",
       "      <td>EH38D4327351</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.468444</td>\n",
       "      <td>chrY</td>\n",
       "      <td>22402568</td>\n",
       "      <td>22402568</td>\n",
       "      <td>ENST00000433481.1</td>\n",
       "      <td>.</td>\n",
       "      <td>-</td>\n",
       "      <td>ENSG00000237902.1</td>\n",
       "      <td>31567</td>\n",
       "      <td>justopen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165066</th>\n",
       "      <td>chrY</td>\n",
       "      <td>26319536</td>\n",
       "      <td>26319816</td>\n",
       "      <td>EH38D4327362</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-10.000000</td>\n",
       "      <td>chrY</td>\n",
       "      <td>26354418</td>\n",
       "      <td>26354418</td>\n",
       "      <td>ENST00000367272.4</td>\n",
       "      <td>.</td>\n",
       "      <td>-</td>\n",
       "      <td>ENSG00000229238.3</td>\n",
       "      <td>34602</td>\n",
       "      <td>justopen</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>165067 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom     start       end         label   1   2   3   4   5   6  ...  \\\n",
       "0       chr1    827342    827691  EH38D2115342 NaN NaN NaN NaN NaN NaN  ...   \n",
       "1       chr1    904594    904931  EH38D2115410 NaN NaN NaN NaN NaN NaN  ...   \n",
       "2       chr1    959147    959495  EH38D2115511 NaN NaN NaN NaN NaN NaN  ...   \n",
       "3       chr1    960392    960733  EH38D2115515 NaN NaN NaN NaN NaN NaN  ...   \n",
       "4       chr1    966292    966617  EH38D2115523 NaN NaN NaN NaN NaN NaN  ...   \n",
       "...      ...       ...       ...           ...  ..  ..  ..  ..  ..  ..  ...   \n",
       "165062  chrY  21602623  21602968  EH38D4327289 NaN NaN NaN NaN NaN NaN  ...   \n",
       "165063  chrY  21840091  21840414  EH38D4327334 NaN NaN NaN NaN NaN NaN  ...   \n",
       "165064  chrY  21845516  21845839  EH38D4327337 NaN NaN NaN NaN NaN NaN  ...   \n",
       "165065  chrY  22370653  22371001  EH38D4327351 NaN NaN NaN NaN NaN NaN  ...   \n",
       "165066  chrY  26319536  26319816  EH38D4327362 NaN NaN NaN NaN NaN NaN  ...   \n",
       "\n",
       "           Z_ctcf  chrom_    start_      end_             label_  score_  \\\n",
       "0        0.175482    chr1    827522    827522  ENST00000473798.1       .   \n",
       "1        1.881979    chr1    904834    904834  ENST00000607769.1       .   \n",
       "2        0.822329    chr1    959290    959290  ENST00000327044.6       .   \n",
       "3      -10.000000    chr1    960587    960587  ENST00000338591.7       .   \n",
       "4        1.973521    chr1    966497    966497  ENST00000379410.7       .   \n",
       "...           ...     ...       ...       ...                ...     ...   \n",
       "165062  -0.656758    chrY  21594666  21594666  ENST00000330337.2       .   \n",
       "165063 -10.000000    chrY  21818218  21818218  ENST00000620993.1       .   \n",
       "165064 -10.000000    chrY  21871331  21871331  ENST00000414540.1       .   \n",
       "165065  -0.468444    chrY  22402568  22402568  ENST00000433481.1       .   \n",
       "165066 -10.000000    chrY  26354418  26354418  ENST00000367272.4       .   \n",
       "\n",
       "        strand_               name_ distance      name  \n",
       "0             -   ENSG00000225880.5        0       pls  \n",
       "1             +   ENSG00000272438.1        0       pls  \n",
       "2             -  ENSG00000188976.10        0       pls  \n",
       "3             +  ENSG00000187961.13        0       pls  \n",
       "4             +  ENSG00000187583.10        0       pls  \n",
       "...         ...                 ...      ...       ...  \n",
       "165062        -   ENSG00000184991.2     7957  justopen  \n",
       "165063        -   ENSG00000277519.1    21873  justopen  \n",
       "165064        +   ENSG00000229725.1    25492  justopen  \n",
       "165065        -   ENSG00000237902.1    31567  justopen  \n",
       "165066        -   ENSG00000229238.3    34602  justopen  \n",
       "\n",
       "[165067 rows x 27 columns]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cre=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/cres/all_cres_encodestyle_pMunion_95atac_95rest.bed', sep='\\t')\n",
    "\n",
    "cre\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "13bc127e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "      <th>chrom_</th>\n",
       "      <th>start_</th>\n",
       "      <th>end_</th>\n",
       "      <th>label_</th>\n",
       "      <th>...</th>\n",
       "      <th>Z_k27ac_</th>\n",
       "      <th>Z_ctcf_</th>\n",
       "      <th>chrom__</th>\n",
       "      <th>start__</th>\n",
       "      <th>end__</th>\n",
       "      <th>label__</th>\n",
       "      <th>score__</th>\n",
       "      <th>strand__</th>\n",
       "      <th>name__</th>\n",
       "      <th>distance_</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name_</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ctcf</th>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>...</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dels</th>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>...</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>justopen</th>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>...</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nels</th>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>...</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "      <td>1101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>openk4</th>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>...</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pels</th>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>...</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "      <td>17588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pls</th>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>...</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          chrom  start    end  score_M  score_mG  score_pG  chrom_  start_  \\\n",
       "name_                                                                        \n",
       "ctcf      11216  11216  11216    11216     11216     11216   11216   11216   \n",
       "dels      24159  24159  24159    24159     24159     24159   24159   24159   \n",
       "justopen  62861  62861  62861    62861     62861     62861   62861   62861   \n",
       "nels       1101   1101   1101     1101      1101      1101    1101    1101   \n",
       "openk4     8318   8318   8318     8318      8318      8318    8318    8318   \n",
       "pels      17588  17588  17588    17588     17588     17588   17588   17588   \n",
       "pls       22103  22103  22103    22103     22103     22103   22103   22103   \n",
       "\n",
       "           end_  label_  ...  Z_k27ac_  Z_ctcf_  chrom__  start__  end__  \\\n",
       "name_                    ...                                               \n",
       "ctcf      11216   11216  ...     11216    11216    11216    11216  11216   \n",
       "dels      24159   24159  ...     24159    24159    24159    24159  24159   \n",
       "justopen  62861   62861  ...     62861    62861    62861    62861  62861   \n",
       "nels       1101    1101  ...      1101     1101     1101     1101   1101   \n",
       "openk4     8318    8318  ...      8318     8318     8318     8318   8318   \n",
       "pels      17588   17588  ...     17588    17588    17588    17588  17588   \n",
       "pls       22103   22103  ...     22103    22103    22103    22103  22103   \n",
       "\n",
       "          label__  score__  strand__  name__  distance_  \n",
       "name_                                                    \n",
       "ctcf        11216    11216     11216   11216      11216  \n",
       "dels        24159    24159     24159   24159      24159  \n",
       "justopen    62861    62861     62861   62861      62861  \n",
       "nels         1101     1101      1101    1101       1101  \n",
       "openk4       8318     8318      8318    8318       8318  \n",
       "pels        17588    17588     17588   17588      17588  \n",
       "pls         22103    22103     22103   22103      22103  \n",
       "\n",
       "[7 rows x 32 columns]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aaa=bf.overlap(uniong1,cre, how='left')\n",
    "aaa.groupby('name_').count()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "91efae5e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "      <th>chrom_</th>\n",
       "      <th>start_</th>\n",
       "      <th>end_</th>\n",
       "      <th>label_</th>\n",
       "      <th>...</th>\n",
       "      <th>chrom__</th>\n",
       "      <th>start__</th>\n",
       "      <th>end__</th>\n",
       "      <th>label__</th>\n",
       "      <th>score__</th>\n",
       "      <th>strand__</th>\n",
       "      <th>name__</th>\n",
       "      <th>distance_</th>\n",
       "      <th>name_</th>\n",
       "      <th>cre</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chrY</td>\n",
       "      <td>26319533</td>\n",
       "      <td>26319755</td>\n",
       "      <td>0.0</td>\n",
       "      <td>342.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>chrY</td>\n",
       "      <td>26319536</td>\n",
       "      <td>26319816</td>\n",
       "      <td>EH38D4327362</td>\n",
       "      <td>...</td>\n",
       "      <td>chrY</td>\n",
       "      <td>26354418.0</td>\n",
       "      <td>26354418.0</td>\n",
       "      <td>ENST00000367272.4</td>\n",
       "      <td>.</td>\n",
       "      <td>-</td>\n",
       "      <td>ENSG00000229238.3</td>\n",
       "      <td>34602.0</td>\n",
       "      <td>justopen</td>\n",
       "      <td>just open</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18090847</td>\n",
       "      <td>18091143</td>\n",
       "      <td>0.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>no cre</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18090171</td>\n",
       "      <td>18090345</td>\n",
       "      <td>0.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>no cre</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18077179</td>\n",
       "      <td>18077421</td>\n",
       "      <td>0.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>no cre</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18074675</td>\n",
       "      <td>18075141</td>\n",
       "      <td>0.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>no cre</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204611</th>\n",
       "      <td>chr16</td>\n",
       "      <td>15153921</td>\n",
       "      <td>15155441</td>\n",
       "      <td>1234.0</td>\n",
       "      <td>960.0</td>\n",
       "      <td>1064.0</td>\n",
       "      <td>chr16</td>\n",
       "      <td>15154796</td>\n",
       "      <td>15155144</td>\n",
       "      <td>EH38D2848055</td>\n",
       "      <td>...</td>\n",
       "      <td>chr16</td>\n",
       "      <td>15154903.0</td>\n",
       "      <td>15154903.0</td>\n",
       "      <td>ENST00000552015.1</td>\n",
       "      <td>.</td>\n",
       "      <td>+</td>\n",
       "      <td>ENSG00000257391.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pls</td>\n",
       "      <td>promoter-like</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204612</th>\n",
       "      <td>chr15</td>\n",
       "      <td>90497848</td>\n",
       "      <td>90498397</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>1404.0</td>\n",
       "      <td>654.0</td>\n",
       "      <td>chr15</td>\n",
       "      <td>90497944</td>\n",
       "      <td>90498294</td>\n",
       "      <td>EH38D2823997</td>\n",
       "      <td>...</td>\n",
       "      <td>chr15</td>\n",
       "      <td>90529925.0</td>\n",
       "      <td>90529925.0</td>\n",
       "      <td>ENST00000420329.6</td>\n",
       "      <td>.</td>\n",
       "      <td>+</td>\n",
       "      <td>ENSG00000140577.15</td>\n",
       "      <td>31631.0</td>\n",
       "      <td>justopen</td>\n",
       "      <td>just open</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204613</th>\n",
       "      <td>chr9</td>\n",
       "      <td>96883802</td>\n",
       "      <td>96884970</td>\n",
       "      <td>1254.0</td>\n",
       "      <td>1433.0</td>\n",
       "      <td>1168.0</td>\n",
       "      <td>chr9</td>\n",
       "      <td>96883987</td>\n",
       "      <td>96884312</td>\n",
       "      <td>EH38D4215738</td>\n",
       "      <td>...</td>\n",
       "      <td>chr9</td>\n",
       "      <td>96910076.0</td>\n",
       "      <td>96910076.0</td>\n",
       "      <td>ENST00000602494.1</td>\n",
       "      <td>.</td>\n",
       "      <td>+</td>\n",
       "      <td>ENSG00000269907.1</td>\n",
       "      <td>25764.0</td>\n",
       "      <td>justopen</td>\n",
       "      <td>just open</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204614</th>\n",
       "      <td>chr9</td>\n",
       "      <td>96883802</td>\n",
       "      <td>96884970</td>\n",
       "      <td>1254.0</td>\n",
       "      <td>1433.0</td>\n",
       "      <td>1168.0</td>\n",
       "      <td>chr9</td>\n",
       "      <td>96884440</td>\n",
       "      <td>96884779</td>\n",
       "      <td>EH38D4215739</td>\n",
       "      <td>...</td>\n",
       "      <td>chr9</td>\n",
       "      <td>96910076.0</td>\n",
       "      <td>96910076.0</td>\n",
       "      <td>ENST00000602494.1</td>\n",
       "      <td>.</td>\n",
       "      <td>+</td>\n",
       "      <td>ENSG00000269907.1</td>\n",
       "      <td>25297.0</td>\n",
       "      <td>justopen</td>\n",
       "      <td>just open</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204615</th>\n",
       "      <td>chr1</td>\n",
       "      <td>206202844</td>\n",
       "      <td>206203880</td>\n",
       "      <td>1373.0</td>\n",
       "      <td>1373.0</td>\n",
       "      <td>1302.0</td>\n",
       "      <td>chr1</td>\n",
       "      <td>206203012</td>\n",
       "      <td>206203280</td>\n",
       "      <td>EH38D2267431</td>\n",
       "      <td>...</td>\n",
       "      <td>chr1</td>\n",
       "      <td>206202873.0</td>\n",
       "      <td>206202873.0</td>\n",
       "      <td>ENST00000367128.7</td>\n",
       "      <td>.</td>\n",
       "      <td>-</td>\n",
       "      <td>ENSG00000196550.10</td>\n",
       "      <td>139.0</td>\n",
       "      <td>pls</td>\n",
       "      <td>promoter-like</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>204616 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        chrom      start        end  score_M  score_mG  score_pG chrom_  \\\n",
       "0        chrY   26319533   26319755      0.0     342.0       0.0   chrY   \n",
       "1       chr20   18090847   18091143      0.0      61.0       0.0   None   \n",
       "2       chr20   18090171   18090345      0.0      77.0       0.0   None   \n",
       "3       chr20   18077179   18077421      0.0      64.0       0.0   None   \n",
       "4       chr20   18074675   18075141      0.0     112.0       0.0   None   \n",
       "...       ...        ...        ...      ...       ...       ...    ...   \n",
       "204611  chr16   15153921   15155441   1234.0     960.0    1064.0  chr16   \n",
       "204612  chr15   90497848   90498397   1250.0    1404.0     654.0  chr15   \n",
       "204613   chr9   96883802   96884970   1254.0    1433.0    1168.0   chr9   \n",
       "204614   chr9   96883802   96884970   1254.0    1433.0    1168.0   chr9   \n",
       "204615   chr1  206202844  206203880   1373.0    1373.0    1302.0   chr1   \n",
       "\n",
       "           start_       end_        label_  ...  chrom__      start__  \\\n",
       "0        26319536   26319816  EH38D4327362  ...     chrY   26354418.0   \n",
       "1            <NA>       <NA>          None  ...     None          NaN   \n",
       "2            <NA>       <NA>          None  ...     None          NaN   \n",
       "3            <NA>       <NA>          None  ...     None          NaN   \n",
       "4            <NA>       <NA>          None  ...     None          NaN   \n",
       "...           ...        ...           ...  ...      ...          ...   \n",
       "204611   15154796   15155144  EH38D2848055  ...    chr16   15154903.0   \n",
       "204612   90497944   90498294  EH38D2823997  ...    chr15   90529925.0   \n",
       "204613   96883987   96884312  EH38D4215738  ...     chr9   96910076.0   \n",
       "204614   96884440   96884779  EH38D4215739  ...     chr9   96910076.0   \n",
       "204615  206203012  206203280  EH38D2267431  ...     chr1  206202873.0   \n",
       "\n",
       "              end__            label__  score__  strand__              name__  \\\n",
       "0        26354418.0  ENST00000367272.4        .         -   ENSG00000229238.3   \n",
       "1               NaN               None     None      None                None   \n",
       "2               NaN               None     None      None                None   \n",
       "3               NaN               None     None      None                None   \n",
       "4               NaN               None     None      None                None   \n",
       "...             ...                ...      ...       ...                 ...   \n",
       "204611   15154903.0  ENST00000552015.1        .         +   ENSG00000257391.1   \n",
       "204612   90529925.0  ENST00000420329.6        .         +  ENSG00000140577.15   \n",
       "204613   96910076.0  ENST00000602494.1        .         +   ENSG00000269907.1   \n",
       "204614   96910076.0  ENST00000602494.1        .         +   ENSG00000269907.1   \n",
       "204615  206202873.0  ENST00000367128.7        .         -  ENSG00000196550.10   \n",
       "\n",
       "        distance_     name_            cre  \n",
       "0         34602.0  justopen      just open  \n",
       "1             NaN      None         no cre  \n",
       "2             NaN      None         no cre  \n",
       "3             NaN      None         no cre  \n",
       "4             NaN      None         no cre  \n",
       "...           ...       ...            ...  \n",
       "204611        0.0       pls  promoter-like  \n",
       "204612    31631.0  justopen      just open  \n",
       "204613    25764.0  justopen      just open  \n",
       "204614    25297.0  justopen      just open  \n",
       "204615      139.0       pls  promoter-like  \n",
       "\n",
       "[204616 rows x 34 columns]"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def cat1(aaa):\n",
    "    if aaa['name_']=='justopen':\n",
    "        return 'just open'\n",
    "    elif aaa['name_']=='ctcf':\n",
    "        return 'ctcf'\n",
    "    elif (aaa['name_']=='nels')|(aaa['name_']=='pels'):\n",
    "        return 'prox. enh'\n",
    "    elif aaa['name_']=='dels':\n",
    "        return 'dist. enh'\n",
    "    elif aaa['name_']=='pls':\n",
    "        return 'promoter-like'\n",
    "    elif aaa['name_']=='openk4':\n",
    "        return 'open K4me3'\n",
    "    else:\n",
    "        return 'no cre'\n",
    "\n",
    "aaa['cre']=aaa.apply(cat1, axis=1) \n",
    "\n",
    "aaa\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "58cfc36c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "      <th>chrom_</th>\n",
       "      <th>start_</th>\n",
       "      <th>end_</th>\n",
       "      <th>label_</th>\n",
       "      <th>...</th>\n",
       "      <th>chrom__</th>\n",
       "      <th>start__</th>\n",
       "      <th>end__</th>\n",
       "      <th>label__</th>\n",
       "      <th>score__</th>\n",
       "      <th>strand__</th>\n",
       "      <th>name__</th>\n",
       "      <th>distance_</th>\n",
       "      <th>name_</th>\n",
       "      <th>cre</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cre_score</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>57270</td>\n",
       "      <td>57270</td>\n",
       "      <td>57270</td>\n",
       "      <td>57270</td>\n",
       "      <td>57270</td>\n",
       "      <td>57270</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>57270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>...</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "      <td>62861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>...</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "      <td>11216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>...</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "      <td>8318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>...</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "      <td>24159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>...</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "      <td>18689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>...</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "      <td>22103</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           chrom  start    end  score_M  score_mG  score_pG  chrom_  start_  \\\n",
       "cre_score                                                                     \n",
       "0          57270  57270  57270    57270     57270     57270       0       0   \n",
       "1          62861  62861  62861    62861     62861     62861   62861   62861   \n",
       "2          11216  11216  11216    11216     11216     11216   11216   11216   \n",
       "3           8318   8318   8318     8318      8318      8318    8318    8318   \n",
       "4          24159  24159  24159    24159     24159     24159   24159   24159   \n",
       "5          18689  18689  18689    18689     18689     18689   18689   18689   \n",
       "6          22103  22103  22103    22103     22103     22103   22103   22103   \n",
       "\n",
       "            end_  label_  ...  chrom__  start__  end__  label__  score__  \\\n",
       "cre_score                 ...                                              \n",
       "0              0       0  ...        0        0      0        0        0   \n",
       "1          62861   62861  ...    62861    62861  62861    62861    62861   \n",
       "2          11216   11216  ...    11216    11216  11216    11216    11216   \n",
       "3           8318    8318  ...     8318     8318   8318     8318     8318   \n",
       "4          24159   24159  ...    24159    24159  24159    24159    24159   \n",
       "5          18689   18689  ...    18689    18689  18689    18689    18689   \n",
       "6          22103   22103  ...    22103    22103  22103    22103    22103   \n",
       "\n",
       "           strand__  name__  distance_  name_    cre  \n",
       "cre_score                                             \n",
       "0                 0       0          0      0  57270  \n",
       "1             62861   62861      62861  62861  62861  \n",
       "2             11216   11216      11216  11216  11216  \n",
       "3              8318    8318       8318   8318   8318  \n",
       "4             24159   24159      24159  24159  24159  \n",
       "5             18689   18689      18689  18689  18689  \n",
       "6             22103   22103      22103  22103  22103  \n",
       "\n",
       "[7 rows x 34 columns]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def cre_score(aaa):\n",
    "    if (aaa['cre'] == 'promoter-like'):\n",
    "        return 6\n",
    "    elif (aaa['cre'] == 'prox. enh') :\n",
    "        return 5\n",
    "    elif (aaa['cre'] == 'dist. enh'):\n",
    "        return 4\n",
    "    elif (aaa['cre'] == 'open K4me3'):\n",
    "        return 3\n",
    "    elif (aaa['cre'] == 'ctcf'):\n",
    "        return 2\n",
    "    elif (aaa['cre'] == 'just open'):\n",
    "        return 1\n",
    "    else:\n",
    "        return 0\n",
    "\n",
    "aaa['cre_score']=aaa.apply(cre_score, axis=1) \n",
    "aaa.groupby('cre_score').count()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "182609ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10271\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "      <th>cre</th>\n",
       "      <th>cre_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18779094</td>\n",
       "      <td>18779327</td>\n",
       "      <td>0.0</td>\n",
       "      <td>224.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>chr20</td>\n",
       "      <td>17715072</td>\n",
       "      <td>17715339</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>chr20</td>\n",
       "      <td>16861815</td>\n",
       "      <td>16862036</td>\n",
       "      <td>0.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>chr20</td>\n",
       "      <td>16821464</td>\n",
       "      <td>16821717</td>\n",
       "      <td>0.0</td>\n",
       "      <td>253.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>chr20</td>\n",
       "      <td>16804022</td>\n",
       "      <td>16804277</td>\n",
       "      <td>0.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120152</th>\n",
       "      <td>chr17</td>\n",
       "      <td>7350933</td>\n",
       "      <td>7352742</td>\n",
       "      <td>282.0</td>\n",
       "      <td>332.0</td>\n",
       "      <td>411.0</td>\n",
       "      <td>promoter-like</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204615</th>\n",
       "      <td>chr1</td>\n",
       "      <td>206202844</td>\n",
       "      <td>206203880</td>\n",
       "      <td>1373.0</td>\n",
       "      <td>1373.0</td>\n",
       "      <td>1302.0</td>\n",
       "      <td>promoter-like</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18058651</td>\n",
       "      <td>18059493</td>\n",
       "      <td>0.0</td>\n",
       "      <td>579.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>promoter-like</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204608</th>\n",
       "      <td>chr7</td>\n",
       "      <td>124929304</td>\n",
       "      <td>124930380</td>\n",
       "      <td>1189.0</td>\n",
       "      <td>1231.0</td>\n",
       "      <td>1237.0</td>\n",
       "      <td>promoter-like</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204550</th>\n",
       "      <td>chr7</td>\n",
       "      <td>102748242</td>\n",
       "      <td>102749775</td>\n",
       "      <td>1110.0</td>\n",
       "      <td>1328.0</td>\n",
       "      <td>1239.0</td>\n",
       "      <td>promoter-like</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>142543 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        chrom      start        end  score_M  score_mG  score_pG  \\\n",
       "54      chr20   18779094   18779327      0.0     224.0       0.0   \n",
       "55      chr20   17715072   17715339      0.0      39.0       0.0   \n",
       "56      chr20   16861815   16862036      0.0     114.0       0.0   \n",
       "57      chr20   16821464   16821717      0.0     253.0       0.0   \n",
       "58      chr20   16804022   16804277      0.0     168.0      83.0   \n",
       "...       ...        ...        ...      ...       ...       ...   \n",
       "120152  chr17    7350933    7352742    282.0     332.0     411.0   \n",
       "204615   chr1  206202844  206203880   1373.0    1373.0    1302.0   \n",
       "5       chr20   18058651   18059493      0.0     579.0     351.0   \n",
       "204608   chr7  124929304  124930380   1189.0    1231.0    1237.0   \n",
       "204550   chr7  102748242  102749775   1110.0    1328.0    1239.0   \n",
       "\n",
       "                  cre  cre_score  \n",
       "54             no cre          0  \n",
       "55             no cre          0  \n",
       "56             no cre          0  \n",
       "57             no cre          0  \n",
       "58             no cre          0  \n",
       "...               ...        ...  \n",
       "120152  promoter-like          6  \n",
       "204615  promoter-like          6  \n",
       "5       promoter-like          6  \n",
       "204608  promoter-like          6  \n",
       "204550  promoter-like          6  \n",
       "\n",
       "[142543 rows x 8 columns]"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#one cre/peak\n",
    "aaa=aaa.fillna(0).sort_values('cre_score').drop_duplicates(subset=['chrom', 'start','end'], keep='last')\n",
    "aaa=aaa[['chrom','start','end','score_M','score_mG','score_pG','cre','cre_score']]\n",
    "\n",
    "#try multiple CREs per peak\n",
    "#aaa=aaa.fillna(0)\n",
    "# aaa=aaa[['chrom','start','end','score_M','score_mG','score_pG','cre','cre_score']]\n",
    "\n",
    "#aaa.to_csv('/home/allana.schooley-umw/as38w/Ranger/cres/all_cres_atpeaks_pMunion_NEWatac_k2785_rest95.bed',sep='\\t')\n",
    "\n",
    "print(len(aaa[aaa['cre_score']==6]))\n",
    "aaa\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "5a2113f8-6c13-4d7d-8745-03f36bfc8f7f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16196 10271\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "      <th>cre_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>59951</th>\n",
       "      <td>chr10</td>\n",
       "      <td>29104588</td>\n",
       "      <td>29106065</td>\n",
       "      <td>0.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60069</th>\n",
       "      <td>chr14</td>\n",
       "      <td>67986450</td>\n",
       "      <td>67987156</td>\n",
       "      <td>0.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>220.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60052</th>\n",
       "      <td>chr14</td>\n",
       "      <td>67990473</td>\n",
       "      <td>67991230</td>\n",
       "      <td>0.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107460</th>\n",
       "      <td>chr18</td>\n",
       "      <td>35456066</td>\n",
       "      <td>35456927</td>\n",
       "      <td>209.0</td>\n",
       "      <td>275.0</td>\n",
       "      <td>220.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107446</th>\n",
       "      <td>chr7</td>\n",
       "      <td>47602340</td>\n",
       "      <td>47602621</td>\n",
       "      <td>209.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>311.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120160</th>\n",
       "      <td>chr1</td>\n",
       "      <td>24416504</td>\n",
       "      <td>24417360</td>\n",
       "      <td>282.0</td>\n",
       "      <td>458.0</td>\n",
       "      <td>413.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98641</th>\n",
       "      <td>chr8</td>\n",
       "      <td>101453899</td>\n",
       "      <td>101454560</td>\n",
       "      <td>155.0</td>\n",
       "      <td>240.0</td>\n",
       "      <td>213.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98657</th>\n",
       "      <td>chr22</td>\n",
       "      <td>35301621</td>\n",
       "      <td>35301959</td>\n",
       "      <td>155.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98676</th>\n",
       "      <td>chr4</td>\n",
       "      <td>1719702</td>\n",
       "      <td>1720915</td>\n",
       "      <td>155.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139637</th>\n",
       "      <td>chr19</td>\n",
       "      <td>41225263</td>\n",
       "      <td>41227136</td>\n",
       "      <td>392.0</td>\n",
       "      <td>423.0</td>\n",
       "      <td>464.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16196 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        chrom      start        end  score_M  score_mG  score_pG  cre_score\n",
       "59951   chr10   29104588   29106065      0.0     315.0       0.0          4\n",
       "60069   chr14   67986450   67987156      0.0     280.0     220.0          4\n",
       "60052   chr14   67990473   67991230      0.0     168.0      95.0          4\n",
       "107460  chr18   35456066   35456927    209.0     275.0     220.0          4\n",
       "107446   chr7   47602340   47602621    209.0     242.0     311.0          4\n",
       "...       ...        ...        ...      ...       ...       ...        ...\n",
       "120160   chr1   24416504   24417360    282.0     458.0     413.0          5\n",
       "98641    chr8  101453899  101454560    155.0     240.0     213.0          5\n",
       "98657   chr22   35301621   35301959    155.0     170.0     110.0          5\n",
       "98676    chr4    1719702    1720915    155.0     143.0     148.0          5\n",
       "139637  chr19   41225263   41227136    392.0     423.0     464.0          5\n",
       "\n",
       "[16196 rows x 7 columns]"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "enh=aaa[(aaa['cre_score']==4)|(aaa['cre_score']==5)]\n",
    "enh=enh[['chrom','start','end','score_M','score_mG','score_pG','cre_score']]\n",
    "\n",
    "prom=aaa[aaa['cre_score']==6]\n",
    "prom=prom[['chrom','start','end','score_M','score_mG','score_pG','cre_score']]\n",
    "\n",
    "print(len(enh),len(prom))\n",
    "enh\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "5b16b1e8-2c78-4f94-8034-39c372f272a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id_index</th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>cluster</th>\n",
       "      <th>size</th>\n",
       "      <th>valency</th>\n",
       "      <th>peak_start</th>\n",
       "      <th>peak_end</th>\n",
       "      <th>size.1</th>\n",
       "      <th>peak_start_ext</th>\n",
       "      <th>peak_end_ext</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>chr1</td>\n",
       "      <td>1020000</td>\n",
       "      <td>1030000</td>\n",
       "      <td>0</td>\n",
       "      <td>30000</td>\n",
       "      <td>3</td>\n",
       "      <td>1010000</td>\n",
       "      <td>1040000</td>\n",
       "      <td>30000</td>\n",
       "      <td>1005000</td>\n",
       "      <td>1045000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>chr1</td>\n",
       "      <td>1900000</td>\n",
       "      <td>1910000</td>\n",
       "      <td>1</td>\n",
       "      <td>30000</td>\n",
       "      <td>2</td>\n",
       "      <td>1890000</td>\n",
       "      <td>1920000</td>\n",
       "      <td>30000</td>\n",
       "      <td>1885000</td>\n",
       "      <td>1925000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>chr1</td>\n",
       "      <td>6600000</td>\n",
       "      <td>6610000</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>2</td>\n",
       "      <td>6590000</td>\n",
       "      <td>6620000</td>\n",
       "      <td>30000</td>\n",
       "      <td>6585000</td>\n",
       "      <td>6625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>chr1</td>\n",
       "      <td>7770000</td>\n",
       "      <td>7780000</td>\n",
       "      <td>3</td>\n",
       "      <td>30000</td>\n",
       "      <td>2</td>\n",
       "      <td>7760000</td>\n",
       "      <td>7790000</td>\n",
       "      <td>30000</td>\n",
       "      <td>7755000</td>\n",
       "      <td>7795000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>chr1</td>\n",
       "      <td>7990000</td>\n",
       "      <td>8000000</td>\n",
       "      <td>4</td>\n",
       "      <td>40000</td>\n",
       "      <td>2</td>\n",
       "      <td>7980000</td>\n",
       "      <td>8020000</td>\n",
       "      <td>40000</td>\n",
       "      <td>7975000</td>\n",
       "      <td>8025000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2100</th>\n",
       "      <td>2100</td>\n",
       "      <td>chr22</td>\n",
       "      <td>45170000</td>\n",
       "      <td>45180000</td>\n",
       "      <td>2100</td>\n",
       "      <td>50000</td>\n",
       "      <td>2</td>\n",
       "      <td>45140000</td>\n",
       "      <td>45190000</td>\n",
       "      <td>50000</td>\n",
       "      <td>45135000</td>\n",
       "      <td>45195000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2101</th>\n",
       "      <td>2101</td>\n",
       "      <td>chr22</td>\n",
       "      <td>46070000</td>\n",
       "      <td>46080000</td>\n",
       "      <td>2101</td>\n",
       "      <td>130000</td>\n",
       "      <td>11</td>\n",
       "      <td>46020000</td>\n",
       "      <td>46150000</td>\n",
       "      <td>130000</td>\n",
       "      <td>46015000</td>\n",
       "      <td>46155000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2102</th>\n",
       "      <td>2102</td>\n",
       "      <td>chr22</td>\n",
       "      <td>46750000</td>\n",
       "      <td>46760000</td>\n",
       "      <td>2102</td>\n",
       "      <td>30000</td>\n",
       "      <td>2</td>\n",
       "      <td>46740000</td>\n",
       "      <td>46770000</td>\n",
       "      <td>30000</td>\n",
       "      <td>46735000</td>\n",
       "      <td>46775000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2103</th>\n",
       "      <td>2103</td>\n",
       "      <td>chr22</td>\n",
       "      <td>49940000</td>\n",
       "      <td>49950000</td>\n",
       "      <td>2103</td>\n",
       "      <td>70000</td>\n",
       "      <td>5</td>\n",
       "      <td>49920000</td>\n",
       "      <td>49990000</td>\n",
       "      <td>70000</td>\n",
       "      <td>49915000</td>\n",
       "      <td>49995000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2104</th>\n",
       "      <td>2104</td>\n",
       "      <td>chr22</td>\n",
       "      <td>50290000</td>\n",
       "      <td>50300000</td>\n",
       "      <td>2104</td>\n",
       "      <td>60000</td>\n",
       "      <td>4</td>\n",
       "      <td>50260000</td>\n",
       "      <td>50320000</td>\n",
       "      <td>60000</td>\n",
       "      <td>50255000</td>\n",
       "      <td>50325000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2105 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id_index  chrom     start       end  cluster    size  valency  \\\n",
       "0            0   chr1   1020000   1030000        0   30000        3   \n",
       "1            1   chr1   1900000   1910000        1   30000        2   \n",
       "2            2   chr1   6600000   6610000        2   30000        2   \n",
       "3            3   chr1   7770000   7780000        3   30000        2   \n",
       "4            4   chr1   7990000   8000000        4   40000        2   \n",
       "...        ...    ...       ...       ...      ...     ...      ...   \n",
       "2100      2100  chr22  45170000  45180000     2100   50000        2   \n",
       "2101      2101  chr22  46070000  46080000     2101  130000       11   \n",
       "2102      2102  chr22  46750000  46760000     2102   30000        2   \n",
       "2103      2103  chr22  49940000  49950000     2103   70000        5   \n",
       "2104      2104  chr22  50290000  50300000     2104   60000        4   \n",
       "\n",
       "      peak_start  peak_end  size.1  peak_start_ext  peak_end_ext  \n",
       "0        1010000   1040000   30000         1005000       1045000  \n",
       "1        1890000   1920000   30000         1885000       1925000  \n",
       "2        6590000   6620000   30000         6585000       6625000  \n",
       "3        7760000   7790000   30000         7755000       7795000  \n",
       "4        7980000   8020000   40000         7975000       8025000  \n",
       "...          ...       ...     ...             ...           ...  \n",
       "2100    45140000  45190000   50000        45135000      45195000  \n",
       "2101    46020000  46150000  130000        46015000      46155000  \n",
       "2102    46740000  46770000   30000        46735000      46775000  \n",
       "2103    49920000  49990000   70000        49915000      49995000  \n",
       "2104    50260000  50320000   60000        50255000      50325000  \n",
       "\n",
       "[2105 rows x 12 columns]"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IDa=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/nativecomps/240314_newIDs/5hr_2X_enrichment.pixel_derived.signal_peaks.bed',sep='\\t')\n",
    "IDa['peak_start_ext']=IDa['peak_start']-5000\n",
    "IDa['peak_end_ext']=IDa['peak_end']+5000\n",
    "IDa=IDa.reset_index(drop=True)\n",
    "IDa=IDa.reset_index().rename(columns={'index':'id_index'})\n",
    "\n",
    "IDa\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "22016f7d-c426-4dcf-b278-f40c5e28e169",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "      <th>cre</th>\n",
       "      <th>cre_score</th>\n",
       "      <th>id_index_id</th>\n",
       "      <th>chrom_id</th>\n",
       "      <th>start_id</th>\n",
       "      <th>end_id</th>\n",
       "      <th>cluster_id</th>\n",
       "      <th>size_id</th>\n",
       "      <th>valency_id</th>\n",
       "      <th>peak_start_id</th>\n",
       "      <th>peak_end_id</th>\n",
       "      <th>size.1_id</th>\n",
       "      <th>peak_start_ext_id</th>\n",
       "      <th>peak_end_ext_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>chr9</td>\n",
       "      <td>112174533</td>\n",
       "      <td>112175583</td>\n",
       "      <td>0.0</td>\n",
       "      <td>291.0</td>\n",
       "      <td>378.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>1295.0</td>\n",
       "      <td>chr9</td>\n",
       "      <td>112150000.0</td>\n",
       "      <td>112160000.0</td>\n",
       "      <td>1295.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>112140000.0</td>\n",
       "      <td>112170000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>112135000</td>\n",
       "      <td>112175000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18279312</td>\n",
       "      <td>18279628</td>\n",
       "      <td>0.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>18270000.0</td>\n",
       "      <td>18280000.0</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>18260000.0</td>\n",
       "      <td>18290000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>18255000</td>\n",
       "      <td>18295000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18272520</td>\n",
       "      <td>18272764</td>\n",
       "      <td>0.0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>18270000.0</td>\n",
       "      <td>18280000.0</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>18260000.0</td>\n",
       "      <td>18290000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>18255000</td>\n",
       "      <td>18295000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18263263</td>\n",
       "      <td>18264156</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1084.0</td>\n",
       "      <td>314.0</td>\n",
       "      <td>ctcf</td>\n",
       "      <td>2</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>18270000.0</td>\n",
       "      <td>18280000.0</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>18260000.0</td>\n",
       "      <td>18290000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>18255000</td>\n",
       "      <td>18295000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>chr9</td>\n",
       "      <td>112360232</td>\n",
       "      <td>112360692</td>\n",
       "      <td>0.0</td>\n",
       "      <td>237.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "      <td>1296.0</td>\n",
       "      <td>chr9</td>\n",
       "      <td>112350000.0</td>\n",
       "      <td>112360000.0</td>\n",
       "      <td>1296.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>112340000.0</td>\n",
       "      <td>112370000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>112335000</td>\n",
       "      <td>112375000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143023</th>\n",
       "      <td>chr3</td>\n",
       "      <td>185807568</td>\n",
       "      <td>185808472</td>\n",
       "      <td>1093.0</td>\n",
       "      <td>1255.0</td>\n",
       "      <td>743.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>571.0</td>\n",
       "      <td>chr3</td>\n",
       "      <td>185800000.0</td>\n",
       "      <td>185810000.0</td>\n",
       "      <td>571.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>185760000.0</td>\n",
       "      <td>185850000.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>185755000</td>\n",
       "      <td>185855000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143030</th>\n",
       "      <td>chr21</td>\n",
       "      <td>14382384</td>\n",
       "      <td>14384213</td>\n",
       "      <td>1110.0</td>\n",
       "      <td>1267.0</td>\n",
       "      <td>1212.0</td>\n",
       "      <td>promoter-like</td>\n",
       "      <td>6</td>\n",
       "      <td>2061.0</td>\n",
       "      <td>chr21</td>\n",
       "      <td>14370000.0</td>\n",
       "      <td>14380000.0</td>\n",
       "      <td>2061.0</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14350000.0</td>\n",
       "      <td>14410000.0</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>14345000</td>\n",
       "      <td>14415000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143035</th>\n",
       "      <td>chr7</td>\n",
       "      <td>25861697</td>\n",
       "      <td>25863276</td>\n",
       "      <td>1117.0</td>\n",
       "      <td>1121.0</td>\n",
       "      <td>1024.0</td>\n",
       "      <td>open K4me3</td>\n",
       "      <td>3</td>\n",
       "      <td>1057.0</td>\n",
       "      <td>chr7</td>\n",
       "      <td>25860000.0</td>\n",
       "      <td>25870000.0</td>\n",
       "      <td>1057.0</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>25830000.0</td>\n",
       "      <td>25890000.0</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>25825000</td>\n",
       "      <td>25895000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143041</th>\n",
       "      <td>chr4</td>\n",
       "      <td>74682349</td>\n",
       "      <td>74683776</td>\n",
       "      <td>1122.0</td>\n",
       "      <td>1280.0</td>\n",
       "      <td>683.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>645.0</td>\n",
       "      <td>chr4</td>\n",
       "      <td>74640000.0</td>\n",
       "      <td>74650000.0</td>\n",
       "      <td>645.0</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>74600000.0</td>\n",
       "      <td>74680000.0</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>74595000</td>\n",
       "      <td>74685000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143047</th>\n",
       "      <td>chr5</td>\n",
       "      <td>90557902</td>\n",
       "      <td>90559422</td>\n",
       "      <td>1133.0</td>\n",
       "      <td>1270.0</td>\n",
       "      <td>1179.0</td>\n",
       "      <td>promoter-like</td>\n",
       "      <td>6</td>\n",
       "      <td>801.0</td>\n",
       "      <td>chr5</td>\n",
       "      <td>90530000.0</td>\n",
       "      <td>90540000.0</td>\n",
       "      <td>801.0</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>90510000.0</td>\n",
       "      <td>90570000.0</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>90505000</td>\n",
       "      <td>90575000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16460 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        chrom      start        end  score_M  score_mG  score_pG  \\\n",
       "31       chr9  112174533  112175583      0.0     291.0     378.0   \n",
       "41      chr20   18279312   18279628      0.0      65.0       0.0   \n",
       "42      chr20   18272520   18272764      0.0     313.0       0.0   \n",
       "43      chr20   18263263   18264156      0.0    1084.0     314.0   \n",
       "69       chr9  112360232  112360692      0.0     237.0       0.0   \n",
       "...       ...        ...        ...      ...       ...       ...   \n",
       "143023   chr3  185807568  185808472   1093.0    1255.0     743.0   \n",
       "143030  chr21   14382384   14384213   1110.0    1267.0    1212.0   \n",
       "143035   chr7   25861697   25863276   1117.0    1121.0    1024.0   \n",
       "143041   chr4   74682349   74683776   1122.0    1280.0     683.0   \n",
       "143047   chr5   90557902   90559422   1133.0    1270.0    1179.0   \n",
       "\n",
       "                  cre  cre_score  id_index_id chrom_id     start_id  \\\n",
       "31          just open          1       1295.0     chr9  112150000.0   \n",
       "41             no cre          0       2045.0    chr20   18270000.0   \n",
       "42          just open          1       2045.0    chr20   18270000.0   \n",
       "43               ctcf          2       2045.0    chr20   18270000.0   \n",
       "69             no cre          0       1296.0     chr9  112350000.0   \n",
       "...               ...        ...          ...      ...          ...   \n",
       "143023      just open          1        571.0     chr3  185800000.0   \n",
       "143030  promoter-like          6       2061.0    chr21   14370000.0   \n",
       "143035     open K4me3          3       1057.0     chr7   25860000.0   \n",
       "143041      dist. enh          4        645.0     chr4   74640000.0   \n",
       "143047  promoter-like          6        801.0     chr5   90530000.0   \n",
       "\n",
       "             end_id  cluster_id  size_id  valency_id  peak_start_id  \\\n",
       "31      112160000.0      1295.0  30000.0         4.0    112140000.0   \n",
       "41       18280000.0      2045.0  30000.0         3.0     18260000.0   \n",
       "42       18280000.0      2045.0  30000.0         3.0     18260000.0   \n",
       "43       18280000.0      2045.0  30000.0         3.0     18260000.0   \n",
       "69      112360000.0      1296.0  30000.0         2.0    112340000.0   \n",
       "...             ...         ...      ...         ...            ...   \n",
       "143023  185810000.0       571.0  90000.0        16.0    185760000.0   \n",
       "143030   14380000.0      2061.0  60000.0         4.0     14350000.0   \n",
       "143035   25870000.0      1057.0  60000.0        11.0     25830000.0   \n",
       "143041   74650000.0       645.0  80000.0        10.0     74600000.0   \n",
       "143047   90540000.0       801.0  60000.0         4.0     90510000.0   \n",
       "\n",
       "        peak_end_id  size.1_id  peak_start_ext_id  peak_end_ext_id  \n",
       "31      112170000.0    30000.0          112135000        112175000  \n",
       "41       18290000.0    30000.0           18255000         18295000  \n",
       "42       18290000.0    30000.0           18255000         18295000  \n",
       "43       18290000.0    30000.0           18255000         18295000  \n",
       "69      112370000.0    30000.0          112335000        112375000  \n",
       "...             ...        ...                ...              ...  \n",
       "143023  185850000.0    90000.0          185755000        185855000  \n",
       "143030   14410000.0    60000.0           14345000         14415000  \n",
       "143035   25890000.0    60000.0           25825000         25895000  \n",
       "143041   74680000.0    80000.0           74595000         74685000  \n",
       "143047   90570000.0    60000.0           90505000         90575000  \n",
       "\n",
       "[16460 rows x 20 columns]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id_cre=bf.overlap(aaa,IDa,cols2=['chrom','peak_start_ext','peak_end_ext'],suffixes=['','_id'],how='left').dropna()\n",
    "id_cre\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "4ae52187-1968-4a11-b312-3d501e4c9fa5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>cluster</th>\n",
       "      <th>size</th>\n",
       "      <th>valency</th>\n",
       "      <th>peak_start</th>\n",
       "      <th>peak_end</th>\n",
       "      <th>size.1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1020000</td>\n",
       "      <td>1030000</td>\n",
       "      <td>0</td>\n",
       "      <td>30000</td>\n",
       "      <td>3</td>\n",
       "      <td>1010000</td>\n",
       "      <td>1040000</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1900000</td>\n",
       "      <td>1910000</td>\n",
       "      <td>1</td>\n",
       "      <td>30000</td>\n",
       "      <td>2</td>\n",
       "      <td>1890000</td>\n",
       "      <td>1920000</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>7990000</td>\n",
       "      <td>8000000</td>\n",
       "      <td>4</td>\n",
       "      <td>40000</td>\n",
       "      <td>2</td>\n",
       "      <td>7980000</td>\n",
       "      <td>8020000</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>chr1</td>\n",
       "      <td>16150000</td>\n",
       "      <td>16160000</td>\n",
       "      <td>7</td>\n",
       "      <td>70000</td>\n",
       "      <td>13</td>\n",
       "      <td>16120000</td>\n",
       "      <td>16190000</td>\n",
       "      <td>70000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>chr1</td>\n",
       "      <td>28520000</td>\n",
       "      <td>28530000</td>\n",
       "      <td>14</td>\n",
       "      <td>50000</td>\n",
       "      <td>4</td>\n",
       "      <td>28500000</td>\n",
       "      <td>28550000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2136</th>\n",
       "      <td>chr22</td>\n",
       "      <td>45170000</td>\n",
       "      <td>45180000</td>\n",
       "      <td>2100</td>\n",
       "      <td>50000</td>\n",
       "      <td>2</td>\n",
       "      <td>45140000</td>\n",
       "      <td>45190000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2137</th>\n",
       "      <td>chr22</td>\n",
       "      <td>46070000</td>\n",
       "      <td>46080000</td>\n",
       "      <td>2101</td>\n",
       "      <td>130000</td>\n",
       "      <td>11</td>\n",
       "      <td>46020000</td>\n",
       "      <td>46150000</td>\n",
       "      <td>130000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2138</th>\n",
       "      <td>chr22</td>\n",
       "      <td>46750000</td>\n",
       "      <td>46760000</td>\n",
       "      <td>2102</td>\n",
       "      <td>30000</td>\n",
       "      <td>2</td>\n",
       "      <td>46740000</td>\n",
       "      <td>46770000</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2139</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49940000</td>\n",
       "      <td>49950000</td>\n",
       "      <td>2103</td>\n",
       "      <td>70000</td>\n",
       "      <td>5</td>\n",
       "      <td>49920000</td>\n",
       "      <td>49990000</td>\n",
       "      <td>70000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2140</th>\n",
       "      <td>chr22</td>\n",
       "      <td>50290000</td>\n",
       "      <td>50300000</td>\n",
       "      <td>2104</td>\n",
       "      <td>60000</td>\n",
       "      <td>4</td>\n",
       "      <td>50260000</td>\n",
       "      <td>50320000</td>\n",
       "      <td>60000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>698 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      chrom     start       end  cluster    size  valency  peak_start  \\\n",
       "0      chr1   1020000   1030000        0   30000        3     1010000   \n",
       "1      chr1   1900000   1910000        1   30000        2     1890000   \n",
       "4      chr1   7990000   8000000        4   40000        2     7980000   \n",
       "7      chr1  16150000  16160000        7   70000       13    16120000   \n",
       "14     chr1  28520000  28530000       14   50000        4    28500000   \n",
       "...     ...       ...       ...      ...     ...      ...         ...   \n",
       "2136  chr22  45170000  45180000     2100   50000        2    45140000   \n",
       "2137  chr22  46070000  46080000     2101  130000       11    46020000   \n",
       "2138  chr22  46750000  46760000     2102   30000        2    46740000   \n",
       "2139  chr22  49940000  49950000     2103   70000        5    49920000   \n",
       "2140  chr22  50290000  50300000     2104   60000        4    50260000   \n",
       "\n",
       "      peak_end  size.1  \n",
       "0      1040000   30000  \n",
       "1      1920000   30000  \n",
       "4      8020000   40000  \n",
       "7     16190000   70000  \n",
       "14    28550000   50000  \n",
       "...        ...     ...  \n",
       "2136  45190000   50000  \n",
       "2137  46150000  130000  \n",
       "2138  46770000   30000  \n",
       "2139  49990000   70000  \n",
       "2140  50320000   60000  \n",
       "\n",
       "[698 rows x 9 columns]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "five=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/nativecomps/240314_newIDs/5hr_2X_enrichment.pixel_derived.signal_peaks.bed',sep='\\t')\n",
    "cyto=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/nativecomps/240314_newIDs/pCyto_2X_enrichment.pixel_derived.signal_peaks.bed',sep='\\t')\n",
    "all_cyto=bf.overlap(IDa,cyto,cols1=['chrom','peak_start','peak_end'],cols2=['chrom','peak_start','peak_end']).dropna().drop_duplicates(['chrom','start','end'])\n",
    "all_cyto=all_cyto[['chrom','start','end','cluster','size','valency','peak_start','peak_end','size.1']]\n",
    "all_cyto\n",
    "#698"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "84410c8c-1572-4ddf-a155-3d2cd8a2d677",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id_index</th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>cluster</th>\n",
       "      <th>size</th>\n",
       "      <th>valency</th>\n",
       "      <th>peak_start</th>\n",
       "      <th>peak_end</th>\n",
       "      <th>size.1</th>\n",
       "      <th>peak_start_ext</th>\n",
       "      <th>peak_end_ext</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>chr1</td>\n",
       "      <td>1020000</td>\n",
       "      <td>1030000</td>\n",
       "      <td>0</td>\n",
       "      <td>30000</td>\n",
       "      <td>3</td>\n",
       "      <td>1010000</td>\n",
       "      <td>1040000</td>\n",
       "      <td>30000</td>\n",
       "      <td>1005000</td>\n",
       "      <td>1045000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>chr1</td>\n",
       "      <td>1900000</td>\n",
       "      <td>1910000</td>\n",
       "      <td>1</td>\n",
       "      <td>30000</td>\n",
       "      <td>2</td>\n",
       "      <td>1890000</td>\n",
       "      <td>1920000</td>\n",
       "      <td>30000</td>\n",
       "      <td>1885000</td>\n",
       "      <td>1925000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>chr1</td>\n",
       "      <td>7990000</td>\n",
       "      <td>8000000</td>\n",
       "      <td>4</td>\n",
       "      <td>40000</td>\n",
       "      <td>2</td>\n",
       "      <td>7980000</td>\n",
       "      <td>8020000</td>\n",
       "      <td>40000</td>\n",
       "      <td>7975000</td>\n",
       "      <td>8025000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>chr1</td>\n",
       "      <td>16150000</td>\n",
       "      <td>16160000</td>\n",
       "      <td>7</td>\n",
       "      <td>70000</td>\n",
       "      <td>13</td>\n",
       "      <td>16120000</td>\n",
       "      <td>16190000</td>\n",
       "      <td>70000</td>\n",
       "      <td>16115000</td>\n",
       "      <td>16195000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>chr1</td>\n",
       "      <td>28520000</td>\n",
       "      <td>28530000</td>\n",
       "      <td>14</td>\n",
       "      <td>50000</td>\n",
       "      <td>4</td>\n",
       "      <td>28500000</td>\n",
       "      <td>28550000</td>\n",
       "      <td>50000</td>\n",
       "      <td>28495000</td>\n",
       "      <td>28555000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>693</th>\n",
       "      <td>693</td>\n",
       "      <td>chr22</td>\n",
       "      <td>45170000</td>\n",
       "      <td>45180000</td>\n",
       "      <td>2100</td>\n",
       "      <td>50000</td>\n",
       "      <td>2</td>\n",
       "      <td>45140000</td>\n",
       "      <td>45190000</td>\n",
       "      <td>50000</td>\n",
       "      <td>45135000</td>\n",
       "      <td>45195000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>694</th>\n",
       "      <td>694</td>\n",
       "      <td>chr22</td>\n",
       "      <td>46070000</td>\n",
       "      <td>46080000</td>\n",
       "      <td>2101</td>\n",
       "      <td>130000</td>\n",
       "      <td>11</td>\n",
       "      <td>46020000</td>\n",
       "      <td>46150000</td>\n",
       "      <td>130000</td>\n",
       "      <td>46015000</td>\n",
       "      <td>46155000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>695</th>\n",
       "      <td>695</td>\n",
       "      <td>chr22</td>\n",
       "      <td>46750000</td>\n",
       "      <td>46760000</td>\n",
       "      <td>2102</td>\n",
       "      <td>30000</td>\n",
       "      <td>2</td>\n",
       "      <td>46740000</td>\n",
       "      <td>46770000</td>\n",
       "      <td>30000</td>\n",
       "      <td>46735000</td>\n",
       "      <td>46775000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>696</th>\n",
       "      <td>696</td>\n",
       "      <td>chr22</td>\n",
       "      <td>49940000</td>\n",
       "      <td>49950000</td>\n",
       "      <td>2103</td>\n",
       "      <td>70000</td>\n",
       "      <td>5</td>\n",
       "      <td>49920000</td>\n",
       "      <td>49990000</td>\n",
       "      <td>70000</td>\n",
       "      <td>49915000</td>\n",
       "      <td>49995000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>697</th>\n",
       "      <td>697</td>\n",
       "      <td>chr22</td>\n",
       "      <td>50290000</td>\n",
       "      <td>50300000</td>\n",
       "      <td>2104</td>\n",
       "      <td>60000</td>\n",
       "      <td>4</td>\n",
       "      <td>50260000</td>\n",
       "      <td>50320000</td>\n",
       "      <td>60000</td>\n",
       "      <td>50255000</td>\n",
       "      <td>50325000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>698 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     id_index  chrom     start       end  cluster    size  valency  \\\n",
       "0           0   chr1   1020000   1030000        0   30000        3   \n",
       "1           1   chr1   1900000   1910000        1   30000        2   \n",
       "2           2   chr1   7990000   8000000        4   40000        2   \n",
       "3           3   chr1  16150000  16160000        7   70000       13   \n",
       "4           4   chr1  28520000  28530000       14   50000        4   \n",
       "..        ...    ...       ...       ...      ...     ...      ...   \n",
       "693       693  chr22  45170000  45180000     2100   50000        2   \n",
       "694       694  chr22  46070000  46080000     2101  130000       11   \n",
       "695       695  chr22  46750000  46760000     2102   30000        2   \n",
       "696       696  chr22  49940000  49950000     2103   70000        5   \n",
       "697       697  chr22  50290000  50300000     2104   60000        4   \n",
       "\n",
       "     peak_start  peak_end  size.1  peak_start_ext  peak_end_ext  \n",
       "0       1010000   1040000   30000         1005000       1045000  \n",
       "1       1890000   1920000   30000         1885000       1925000  \n",
       "2       7980000   8020000   40000         7975000       8025000  \n",
       "3      16120000  16190000   70000        16115000      16195000  \n",
       "4      28500000  28550000   50000        28495000      28555000  \n",
       "..          ...       ...     ...             ...           ...  \n",
       "693    45140000  45190000   50000        45135000      45195000  \n",
       "694    46020000  46150000  130000        46015000      46155000  \n",
       "695    46740000  46770000   30000        46735000      46775000  \n",
       "696    49920000  49990000   70000        49915000      49995000  \n",
       "697    50260000  50320000   60000        50255000      50325000  \n",
       "\n",
       "[698 rows x 12 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# IDc=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/nativecomps/240314_newIDs/pCyto_2X_enrichment.pixel_derived.signal_peaks.bed',sep='\\t')\n",
    "IDc=all_cyto\n",
    "IDc['peak_start_ext']=IDc['peak_start']-5000\n",
    "IDc['peak_end_ext']=IDc['peak_end']+5000\n",
    "IDc=IDc.reset_index(drop=True)\n",
    "IDc=IDc.reset_index().rename(columns={'index':'id_index'})\n",
    "\n",
    "# ID_peaks=bf.overlap(IDa,uniong1,how='left',suffixes=['','_atac'])\n",
    "# ID_peaks\n",
    "IDc\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "b53d6a0e-197c-4dc8-ab9d-6dace6e939f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "      <th>cre</th>\n",
       "      <th>cre_score</th>\n",
       "      <th>id_index_id</th>\n",
       "      <th>chrom_id</th>\n",
       "      <th>start_id</th>\n",
       "      <th>end_id</th>\n",
       "      <th>cluster_id</th>\n",
       "      <th>size_id</th>\n",
       "      <th>valency_id</th>\n",
       "      <th>peak_start_id</th>\n",
       "      <th>peak_end_id</th>\n",
       "      <th>size.1_id</th>\n",
       "      <th>peak_start_ext_id</th>\n",
       "      <th>peak_end_ext_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>chr20</td>\n",
       "      <td>10708219</td>\n",
       "      <td>10709212</td>\n",
       "      <td>0.0</td>\n",
       "      <td>323.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>674.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>10660000.0</td>\n",
       "      <td>10670000.0</td>\n",
       "      <td>2042.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10640000.0</td>\n",
       "      <td>10710000.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>10635000</td>\n",
       "      <td>10715000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>chr20</td>\n",
       "      <td>10670695</td>\n",
       "      <td>10670949</td>\n",
       "      <td>0.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>674.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>10660000.0</td>\n",
       "      <td>10670000.0</td>\n",
       "      <td>2042.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10640000.0</td>\n",
       "      <td>10710000.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>10635000</td>\n",
       "      <td>10715000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>chr20</td>\n",
       "      <td>10664319</td>\n",
       "      <td>10665432</td>\n",
       "      <td>0.0</td>\n",
       "      <td>166.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>674.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>10660000.0</td>\n",
       "      <td>10670000.0</td>\n",
       "      <td>2042.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10640000.0</td>\n",
       "      <td>10710000.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>10635000</td>\n",
       "      <td>10715000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>chr20</td>\n",
       "      <td>10661520</td>\n",
       "      <td>10661815</td>\n",
       "      <td>0.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>674.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>10660000.0</td>\n",
       "      <td>10670000.0</td>\n",
       "      <td>2042.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10640000.0</td>\n",
       "      <td>10710000.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>10635000</td>\n",
       "      <td>10715000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>chr20</td>\n",
       "      <td>10660688</td>\n",
       "      <td>10660994</td>\n",
       "      <td>0.0</td>\n",
       "      <td>319.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>674.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>10660000.0</td>\n",
       "      <td>10670000.0</td>\n",
       "      <td>2042.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10640000.0</td>\n",
       "      <td>10710000.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>10635000</td>\n",
       "      <td>10715000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142798</th>\n",
       "      <td>chr21</td>\n",
       "      <td>37338463</td>\n",
       "      <td>37339506</td>\n",
       "      <td>1025.0</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>1086.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>683.0</td>\n",
       "      <td>chr21</td>\n",
       "      <td>37350000.0</td>\n",
       "      <td>37360000.0</td>\n",
       "      <td>2080.0</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>37330000.0</td>\n",
       "      <td>37390000.0</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>37325000</td>\n",
       "      <td>37395000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142813</th>\n",
       "      <td>chr14</td>\n",
       "      <td>52706170</td>\n",
       "      <td>52707801</td>\n",
       "      <td>1035.0</td>\n",
       "      <td>1044.0</td>\n",
       "      <td>1113.0</td>\n",
       "      <td>promoter-like</td>\n",
       "      <td>6</td>\n",
       "      <td>559.0</td>\n",
       "      <td>chr14</td>\n",
       "      <td>52710000.0</td>\n",
       "      <td>52720000.0</td>\n",
       "      <td>1730.0</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>52670000.0</td>\n",
       "      <td>52750000.0</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>52665000</td>\n",
       "      <td>52755000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142865</th>\n",
       "      <td>chr3</td>\n",
       "      <td>185807568</td>\n",
       "      <td>185808472</td>\n",
       "      <td>1093.0</td>\n",
       "      <td>1255.0</td>\n",
       "      <td>743.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>185.0</td>\n",
       "      <td>chr3</td>\n",
       "      <td>185800000.0</td>\n",
       "      <td>185810000.0</td>\n",
       "      <td>571.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>185760000.0</td>\n",
       "      <td>185850000.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>185755000</td>\n",
       "      <td>185855000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142877</th>\n",
       "      <td>chr7</td>\n",
       "      <td>25861697</td>\n",
       "      <td>25863276</td>\n",
       "      <td>1117.0</td>\n",
       "      <td>1121.0</td>\n",
       "      <td>1024.0</td>\n",
       "      <td>open K4me3</td>\n",
       "      <td>3</td>\n",
       "      <td>342.0</td>\n",
       "      <td>chr7</td>\n",
       "      <td>25860000.0</td>\n",
       "      <td>25870000.0</td>\n",
       "      <td>1057.0</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>25830000.0</td>\n",
       "      <td>25890000.0</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>25825000</td>\n",
       "      <td>25895000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142883</th>\n",
       "      <td>chr4</td>\n",
       "      <td>74682349</td>\n",
       "      <td>74683776</td>\n",
       "      <td>1122.0</td>\n",
       "      <td>1280.0</td>\n",
       "      <td>683.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>213.0</td>\n",
       "      <td>chr4</td>\n",
       "      <td>74640000.0</td>\n",
       "      <td>74650000.0</td>\n",
       "      <td>645.0</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>74600000.0</td>\n",
       "      <td>74680000.0</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>74595000</td>\n",
       "      <td>74685000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7876 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        chrom      start        end  score_M  score_mG  score_pG  \\\n",
       "255     chr20   10708219   10709212      0.0     323.0       0.0   \n",
       "256     chr20   10670695   10670949      0.0      62.0       0.0   \n",
       "257     chr20   10664319   10665432      0.0     166.0     101.0   \n",
       "258     chr20   10661520   10661815      0.0      86.0       0.0   \n",
       "259     chr20   10660688   10660994      0.0     319.0     159.0   \n",
       "...       ...        ...        ...      ...       ...       ...   \n",
       "142798  chr21   37338463   37339506   1025.0    1068.0    1086.0   \n",
       "142813  chr14   52706170   52707801   1035.0    1044.0    1113.0   \n",
       "142865   chr3  185807568  185808472   1093.0    1255.0     743.0   \n",
       "142877   chr7   25861697   25863276   1117.0    1121.0    1024.0   \n",
       "142883   chr4   74682349   74683776   1122.0    1280.0     683.0   \n",
       "\n",
       "                  cre  cre_score  id_index_id chrom_id     start_id  \\\n",
       "255         dist. enh          4        674.0    chr20   10660000.0   \n",
       "256         dist. enh          4        674.0    chr20   10660000.0   \n",
       "257         dist. enh          4        674.0    chr20   10660000.0   \n",
       "258         dist. enh          4        674.0    chr20   10660000.0   \n",
       "259         dist. enh          4        674.0    chr20   10660000.0   \n",
       "...               ...        ...          ...      ...          ...   \n",
       "142798      just open          1        683.0    chr21   37350000.0   \n",
       "142813  promoter-like          6        559.0    chr14   52710000.0   \n",
       "142865      just open          1        185.0     chr3  185800000.0   \n",
       "142877     open K4me3          3        342.0     chr7   25860000.0   \n",
       "142883      dist. enh          4        213.0     chr4   74640000.0   \n",
       "\n",
       "             end_id  cluster_id  size_id  valency_id  peak_start_id  \\\n",
       "255      10670000.0      2042.0  70000.0        10.0     10640000.0   \n",
       "256      10670000.0      2042.0  70000.0        10.0     10640000.0   \n",
       "257      10670000.0      2042.0  70000.0        10.0     10640000.0   \n",
       "258      10670000.0      2042.0  70000.0        10.0     10640000.0   \n",
       "259      10670000.0      2042.0  70000.0        10.0     10640000.0   \n",
       "...             ...         ...      ...         ...            ...   \n",
       "142798   37360000.0      2080.0  60000.0         7.0     37330000.0   \n",
       "142813   52720000.0      1730.0  80000.0        14.0     52670000.0   \n",
       "142865  185810000.0       571.0  90000.0        16.0    185760000.0   \n",
       "142877   25870000.0      1057.0  60000.0        11.0     25830000.0   \n",
       "142883   74650000.0       645.0  80000.0        10.0     74600000.0   \n",
       "\n",
       "        peak_end_id  size.1_id  peak_start_ext_id  peak_end_ext_id  \n",
       "255      10710000.0    70000.0           10635000         10715000  \n",
       "256      10710000.0    70000.0           10635000         10715000  \n",
       "257      10710000.0    70000.0           10635000         10715000  \n",
       "258      10710000.0    70000.0           10635000         10715000  \n",
       "259      10710000.0    70000.0           10635000         10715000  \n",
       "...             ...        ...                ...              ...  \n",
       "142798   37390000.0    60000.0           37325000         37395000  \n",
       "142813   52750000.0    80000.0           52665000         52755000  \n",
       "142865  185850000.0    90000.0          185755000        185855000  \n",
       "142877   25890000.0    60000.0           25825000         25895000  \n",
       "142883   74680000.0    80000.0           74595000         74685000  \n",
       "\n",
       "[7876 rows x 20 columns]"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id_cre_c=bf.overlap(aaa,IDc,cols2=['chrom','peak_start_ext','peak_end_ext'],suffixes=['','_id'],how='left').dropna()\n",
    "id_cre_c\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "7580e10a-351f-4c39-8a14-72a89686bc96",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "11110 9631\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>strand</th>\n",
       "      <th>name</th>\n",
       "      <th>start_Rseq</th>\n",
       "      <th>en_Rseq</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>FPKM</th>\n",
       "      <th>TPM</th>\n",
       "      <th>TSS_start</th>\n",
       "      <th>TSS_end</th>\n",
       "      <th>TSS_start_ext</th>\n",
       "      <th>TSS_end_ext</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr16</td>\n",
       "      <td>85792414</td>\n",
       "      <td>85792933</td>\n",
       "      <td>+</td>\n",
       "      <td>LOC101928557</td>\n",
       "      <td>85792415</td>\n",
       "      <td>85792933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85792413</td>\n",
       "      <td>85792415</td>\n",
       "      <td>85787413</td>\n",
       "      <td>85797415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr14</td>\n",
       "      <td>24505352</td>\n",
       "      <td>24508265</td>\n",
       "      <td>-</td>\n",
       "      <td>CMA1</td>\n",
       "      <td>24505353</td>\n",
       "      <td>24508265</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24508264</td>\n",
       "      <td>24508266</td>\n",
       "      <td>24503264</td>\n",
       "      <td>24513266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr12</td>\n",
       "      <td>1791962</td>\n",
       "      <td>1918652</td>\n",
       "      <td>-</td>\n",
       "      <td>CACNA2D4</td>\n",
       "      <td>1791963</td>\n",
       "      <td>1918652</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1918651</td>\n",
       "      <td>1918653</td>\n",
       "      <td>1913651</td>\n",
       "      <td>1923653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr21</td>\n",
       "      <td>6560690</td>\n",
       "      <td>6564494</td>\n",
       "      <td>+</td>\n",
       "      <td>CRYAA</td>\n",
       "      <td>6560691</td>\n",
       "      <td>6564494</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6560689</td>\n",
       "      <td>6560691</td>\n",
       "      <td>6555689</td>\n",
       "      <td>6565691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>chr2</td>\n",
       "      <td>41931598</td>\n",
       "      <td>41933723</td>\n",
       "      <td>-</td>\n",
       "      <td>LINC01914</td>\n",
       "      <td>41931599</td>\n",
       "      <td>41933723</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>41933722</td>\n",
       "      <td>41933724</td>\n",
       "      <td>41928722</td>\n",
       "      <td>41938724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28213</th>\n",
       "      <td>chr14</td>\n",
       "      <td>20343070</td>\n",
       "      <td>20343411</td>\n",
       "      <td>-</td>\n",
       "      <td>RPPH1</td>\n",
       "      <td>20343071</td>\n",
       "      <td>20343411</td>\n",
       "      <td>133232.234375</td>\n",
       "      <td>7654.960449</td>\n",
       "      <td>16225.344727</td>\n",
       "      <td>20343410</td>\n",
       "      <td>20343412</td>\n",
       "      <td>20338410</td>\n",
       "      <td>20348412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28214</th>\n",
       "      <td>chr9</td>\n",
       "      <td>35657750</td>\n",
       "      <td>35658018</td>\n",
       "      <td>-</td>\n",
       "      <td>RMRP</td>\n",
       "      <td>35657751</td>\n",
       "      <td>35658018</td>\n",
       "      <td>352675.84375</td>\n",
       "      <td>20263.261719</td>\n",
       "      <td>42949.722656</td>\n",
       "      <td>35658017</td>\n",
       "      <td>35658019</td>\n",
       "      <td>35653017</td>\n",
       "      <td>35663019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28215</th>\n",
       "      <td>chr6</td>\n",
       "      <td>52995619</td>\n",
       "      <td>52995951</td>\n",
       "      <td>+</td>\n",
       "      <td>RN7SK</td>\n",
       "      <td>52995620</td>\n",
       "      <td>52995951</td>\n",
       "      <td>393670.25</td>\n",
       "      <td>22618.626953</td>\n",
       "      <td>47942.121094</td>\n",
       "      <td>52995618</td>\n",
       "      <td>52995620</td>\n",
       "      <td>52990618</td>\n",
       "      <td>53000620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28216</th>\n",
       "      <td>chr14</td>\n",
       "      <td>49586579</td>\n",
       "      <td>49586878</td>\n",
       "      <td>+</td>\n",
       "      <td>RN7SL1</td>\n",
       "      <td>49586580</td>\n",
       "      <td>49586878</td>\n",
       "      <td>467574.59375</td>\n",
       "      <td>26864.857422</td>\n",
       "      <td>56942.371094</td>\n",
       "      <td>49586578</td>\n",
       "      <td>49586580</td>\n",
       "      <td>49581578</td>\n",
       "      <td>49591580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28217</th>\n",
       "      <td>chr14</td>\n",
       "      <td>49862550</td>\n",
       "      <td>49862849</td>\n",
       "      <td>-</td>\n",
       "      <td>RN7SL2</td>\n",
       "      <td>49862551</td>\n",
       "      <td>49862849</td>\n",
       "      <td>551316.875</td>\n",
       "      <td>31676.333984</td>\n",
       "      <td>67140.710938</td>\n",
       "      <td>49862848</td>\n",
       "      <td>49862850</td>\n",
       "      <td>49857848</td>\n",
       "      <td>49867850</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>27424 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom     start       end strand          name start_Rseq   en_Rseq  \\\n",
       "1      chr16  85792414  85792933      +  LOC101928557   85792415  85792933   \n",
       "2      chr14  24505352  24508265      -          CMA1   24505353  24508265   \n",
       "3      chr12   1791962   1918652      -      CACNA2D4    1791963   1918652   \n",
       "4      chr21   6560690   6564494      +         CRYAA    6560691   6564494   \n",
       "5       chr2  41931598  41933723      -     LINC01914   41931599  41933723   \n",
       "...      ...       ...       ...    ...           ...        ...       ...   \n",
       "28213  chr14  20343070  20343411      -         RPPH1   20343071  20343411   \n",
       "28214   chr9  35657750  35658018      -          RMRP   35657751  35658018   \n",
       "28215   chr6  52995619  52995951      +         RN7SK   52995620  52995951   \n",
       "28216  chr14  49586579  49586878      +        RN7SL1   49586580  49586878   \n",
       "28217  chr14  49862550  49862849      -        RN7SL2   49862551  49862849   \n",
       "\n",
       "            Coverage          FPKM           TPM  TSS_start   TSS_end  \\\n",
       "1                0.0      0.000000           0.0   85792413  85792415   \n",
       "2                0.0      0.000000           0.0   24508264  24508266   \n",
       "3                0.0      0.000000           0.0    1918651   1918653   \n",
       "4                0.0      0.000000           0.0    6560689   6560691   \n",
       "5                0.0      0.000000           0.0   41933722  41933724   \n",
       "...              ...           ...           ...        ...       ...   \n",
       "28213  133232.234375   7654.960449  16225.344727   20343410  20343412   \n",
       "28214   352675.84375  20263.261719  42949.722656   35658017  35658019   \n",
       "28215      393670.25  22618.626953  47942.121094   52995618  52995620   \n",
       "28216   467574.59375  26864.857422  56942.371094   49586578  49586580   \n",
       "28217     551316.875  31676.333984  67140.710938   49862848  49862850   \n",
       "\n",
       "       TSS_start_ext  TSS_end_ext  \n",
       "1           85787413     85797415  \n",
       "2           24503264     24513266  \n",
       "3            1913651      1923653  \n",
       "4            6555689      6565691  \n",
       "5           41928722     41938724  \n",
       "...              ...          ...  \n",
       "28213       20338410     20348412  \n",
       "28214       35653017     35663019  \n",
       "28215       52990618     53000620  \n",
       "28216       49581578     49591580  \n",
       "28217       49857848     49867850  \n",
       "\n",
       "[27424 rows x 14 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#table crossed with on genes. NB strands are already flipped\n",
    "genes=pd.read_csv('/home/allana.schooley-umw/as38w/Ranger/RNAseq/RG0-FPKM.at.hg38.refGene.exons.reducedchroms.bed',sep='\\t', \\\n",
    "                  names=['chrom','start','end','strand','name','start_Rseq','en_Rseq','Coverage','FPKM','TPM','TSS_start','TSS_end','TSS_start_ext','TSS_end_ext'])\n",
    "chroms=['chr1','chr2','chr3','chr4','chr5','chr6','chr7','chr8','chr9','chr10','chr11','chr12','chr13','chr14','chr15','chr16','chr17','chr18','chr19','chr20','chr21','chr22']\n",
    "genes=genes[genes['chrom'].isin(chroms)].drop_duplicates(subset=['chrom','start','end'])\n",
    "\n",
    "\n",
    "genes['TSS_start']=genes['TSS_start'].astype(int)\n",
    "genes['TSS_end']=genes['TSS_end'].astype(int)\n",
    "genes['TSS_start_ext']=genes['TSS_start']-5000\n",
    "genes['TSS_end_ext']=genes['TSS_end']+5000\n",
    "genes['FPKM']=genes['FPKM'].astype(float)\n",
    "\n",
    "print(len(genes[genes['FPKM']>1]),len(genes[genes['FPKM']==0]))\n",
    "genes\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "d4610f7f-e841-449e-ba69-bf22c9495850",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "      <th>cre</th>\n",
       "      <th>cre_score</th>\n",
       "      <th>id_index_id</th>\n",
       "      <th>chrom_id</th>\n",
       "      <th>...</th>\n",
       "      <th>name_</th>\n",
       "      <th>start_Rseq_</th>\n",
       "      <th>en_Rseq_</th>\n",
       "      <th>Coverage_</th>\n",
       "      <th>FPKM_</th>\n",
       "      <th>TPM_</th>\n",
       "      <th>TSS_start_</th>\n",
       "      <th>TSS_end_</th>\n",
       "      <th>TSS_start_ext_</th>\n",
       "      <th>TSS_end_ext_</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr9</td>\n",
       "      <td>112174533</td>\n",
       "      <td>112175583</td>\n",
       "      <td>0.0</td>\n",
       "      <td>291.0</td>\n",
       "      <td>378.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>1295.0</td>\n",
       "      <td>chr9</td>\n",
       "      <td>...</td>\n",
       "      <td>SUSD1</td>\n",
       "      <td>112040783</td>\n",
       "      <td>112175297</td>\n",
       "      <td>170.895981</td>\n",
       "      <td>10.023834</td>\n",
       "      <td>21.246378</td>\n",
       "      <td>112175296</td>\n",
       "      <td>112175298</td>\n",
       "      <td>112170296.0</td>\n",
       "      <td>112180298.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18279312</td>\n",
       "      <td>18279628</td>\n",
       "      <td>0.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18272520</td>\n",
       "      <td>18272764</td>\n",
       "      <td>0.0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18263263</td>\n",
       "      <td>18264156</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1084.0</td>\n",
       "      <td>314.0</td>\n",
       "      <td>ctcf</td>\n",
       "      <td>2</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr9</td>\n",
       "      <td>112360232</td>\n",
       "      <td>112360692</td>\n",
       "      <td>0.0</td>\n",
       "      <td>237.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "      <td>1296.0</td>\n",
       "      <td>chr9</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17055</th>\n",
       "      <td>chr3</td>\n",
       "      <td>185807568</td>\n",
       "      <td>185808472</td>\n",
       "      <td>1093.0</td>\n",
       "      <td>1255.0</td>\n",
       "      <td>743.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>571.0</td>\n",
       "      <td>chr3</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17056</th>\n",
       "      <td>chr21</td>\n",
       "      <td>14382384</td>\n",
       "      <td>14384213</td>\n",
       "      <td>1110.0</td>\n",
       "      <td>1267.0</td>\n",
       "      <td>1212.0</td>\n",
       "      <td>promoter-like</td>\n",
       "      <td>6</td>\n",
       "      <td>2061.0</td>\n",
       "      <td>chr21</td>\n",
       "      <td>...</td>\n",
       "      <td>HSPA13</td>\n",
       "      <td>14371116</td>\n",
       "      <td>14383146</td>\n",
       "      <td>170.593094</td>\n",
       "      <td>9.801558</td>\n",
       "      <td>20.775242</td>\n",
       "      <td>14383145</td>\n",
       "      <td>14383147</td>\n",
       "      <td>14378145.0</td>\n",
       "      <td>14388147.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17057</th>\n",
       "      <td>chr7</td>\n",
       "      <td>25861697</td>\n",
       "      <td>25863276</td>\n",
       "      <td>1117.0</td>\n",
       "      <td>1121.0</td>\n",
       "      <td>1024.0</td>\n",
       "      <td>open K4me3</td>\n",
       "      <td>3</td>\n",
       "      <td>1057.0</td>\n",
       "      <td>chr7</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17058</th>\n",
       "      <td>chr4</td>\n",
       "      <td>74682349</td>\n",
       "      <td>74683776</td>\n",
       "      <td>1122.0</td>\n",
       "      <td>1280.0</td>\n",
       "      <td>683.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>645.0</td>\n",
       "      <td>chr4</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17059</th>\n",
       "      <td>chr5</td>\n",
       "      <td>90557902</td>\n",
       "      <td>90559422</td>\n",
       "      <td>1133.0</td>\n",
       "      <td>1270.0</td>\n",
       "      <td>1179.0</td>\n",
       "      <td>promoter-like</td>\n",
       "      <td>6</td>\n",
       "      <td>801.0</td>\n",
       "      <td>chr5</td>\n",
       "      <td>...</td>\n",
       "      <td>ADGRV1</td>\n",
       "      <td>90558797</td>\n",
       "      <td>91164437</td>\n",
       "      <td>23.6957</td>\n",
       "      <td>1.364265</td>\n",
       "      <td>2.891676</td>\n",
       "      <td>90558795</td>\n",
       "      <td>90558797</td>\n",
       "      <td>90553795.0</td>\n",
       "      <td>90563797.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>17060 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom      start        end  score_M  score_mG  score_pG  \\\n",
       "0       chr9  112174533  112175583      0.0     291.0     378.0   \n",
       "1      chr20   18279312   18279628      0.0      65.0       0.0   \n",
       "2      chr20   18272520   18272764      0.0     313.0       0.0   \n",
       "3      chr20   18263263   18264156      0.0    1084.0     314.0   \n",
       "4       chr9  112360232  112360692      0.0     237.0       0.0   \n",
       "...      ...        ...        ...      ...       ...       ...   \n",
       "17055   chr3  185807568  185808472   1093.0    1255.0     743.0   \n",
       "17056  chr21   14382384   14384213   1110.0    1267.0    1212.0   \n",
       "17057   chr7   25861697   25863276   1117.0    1121.0    1024.0   \n",
       "17058   chr4   74682349   74683776   1122.0    1280.0     683.0   \n",
       "17059   chr5   90557902   90559422   1133.0    1270.0    1179.0   \n",
       "\n",
       "                 cre  cre_score  id_index_id chrom_id  ...   name_  \\\n",
       "0          just open          1       1295.0     chr9  ...   SUSD1   \n",
       "1             no cre          0       2045.0    chr20  ...    None   \n",
       "2          just open          1       2045.0    chr20  ...    None   \n",
       "3               ctcf          2       2045.0    chr20  ...    None   \n",
       "4             no cre          0       1296.0     chr9  ...    None   \n",
       "...              ...        ...          ...      ...  ...     ...   \n",
       "17055      just open          1        571.0     chr3  ...    None   \n",
       "17056  promoter-like          6       2061.0    chr21  ...  HSPA13   \n",
       "17057     open K4me3          3       1057.0     chr7  ...    None   \n",
       "17058      dist. enh          4        645.0     chr4  ...    None   \n",
       "17059  promoter-like          6        801.0     chr5  ...  ADGRV1   \n",
       "\n",
       "       start_Rseq_   en_Rseq_   Coverage_      FPKM_       TPM_  TSS_start_  \\\n",
       "0        112040783  112175297  170.895981  10.023834  21.246378   112175296   \n",
       "1             None       None        None        NaN       None        <NA>   \n",
       "2             None       None        None        NaN       None        <NA>   \n",
       "3             None       None        None        NaN       None        <NA>   \n",
       "4             None       None        None        NaN       None        <NA>   \n",
       "...            ...        ...         ...        ...        ...         ...   \n",
       "17055         None       None        None        NaN       None        <NA>   \n",
       "17056     14371116   14383146  170.593094   9.801558  20.775242    14383145   \n",
       "17057         None       None        None        NaN       None        <NA>   \n",
       "17058         None       None        None        NaN       None        <NA>   \n",
       "17059     90558797   91164437     23.6957   1.364265   2.891676    90558795   \n",
       "\n",
       "        TSS_end_  TSS_start_ext_  TSS_end_ext_  \n",
       "0      112175298     112170296.0   112180298.0  \n",
       "1           <NA>             NaN           NaN  \n",
       "2           <NA>             NaN           NaN  \n",
       "3           <NA>             NaN           NaN  \n",
       "4           <NA>             NaN           NaN  \n",
       "...          ...             ...           ...  \n",
       "17055       <NA>             NaN           NaN  \n",
       "17056   14383147      14378145.0    14388147.0  \n",
       "17057       <NA>             NaN           NaN  \n",
       "17058       <NA>             NaN           NaN  \n",
       "17059   90558797      90553795.0    90563797.0  \n",
       "\n",
       "[17060 rows x 34 columns]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cre_genes=bf.overlap(id_cre,genes,cols2=['chrom','TSS_start','TSS_end'],how='left')\n",
    "\n",
    "cre_genes\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "64e520de-b1af-4cf0-aea0-4d6a03cfe32e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "      <th>cre</th>\n",
       "      <th>cre_score</th>\n",
       "      <th>id_index_id</th>\n",
       "      <th>chrom_id</th>\n",
       "      <th>...</th>\n",
       "      <th>name_</th>\n",
       "      <th>start_Rseq_</th>\n",
       "      <th>en_Rseq_</th>\n",
       "      <th>Coverage_</th>\n",
       "      <th>FPKM_</th>\n",
       "      <th>TPM_</th>\n",
       "      <th>TSS_start_</th>\n",
       "      <th>TSS_end_</th>\n",
       "      <th>TSS_start_ext_</th>\n",
       "      <th>TSS_end_ext_</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr20</td>\n",
       "      <td>10708219</td>\n",
       "      <td>10709212</td>\n",
       "      <td>0.0</td>\n",
       "      <td>323.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>674.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr20</td>\n",
       "      <td>10670695</td>\n",
       "      <td>10670949</td>\n",
       "      <td>0.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>674.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr20</td>\n",
       "      <td>10664319</td>\n",
       "      <td>10665432</td>\n",
       "      <td>0.0</td>\n",
       "      <td>166.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>674.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr20</td>\n",
       "      <td>10661520</td>\n",
       "      <td>10661815</td>\n",
       "      <td>0.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>674.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr20</td>\n",
       "      <td>10660688</td>\n",
       "      <td>10660994</td>\n",
       "      <td>0.0</td>\n",
       "      <td>319.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>674.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8151</th>\n",
       "      <td>chr21</td>\n",
       "      <td>37338463</td>\n",
       "      <td>37339506</td>\n",
       "      <td>1025.0</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>1086.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>683.0</td>\n",
       "      <td>chr21</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8152</th>\n",
       "      <td>chr14</td>\n",
       "      <td>52706170</td>\n",
       "      <td>52707801</td>\n",
       "      <td>1035.0</td>\n",
       "      <td>1044.0</td>\n",
       "      <td>1113.0</td>\n",
       "      <td>promoter-like</td>\n",
       "      <td>6</td>\n",
       "      <td>559.0</td>\n",
       "      <td>chr14</td>\n",
       "      <td>...</td>\n",
       "      <td>PSMC6</td>\n",
       "      <td>52707200</td>\n",
       "      <td>52728590</td>\n",
       "      <td>567.687866</td>\n",
       "      <td>55.392612</td>\n",
       "      <td>117.409393</td>\n",
       "      <td>52707198</td>\n",
       "      <td>52707200</td>\n",
       "      <td>52702198.0</td>\n",
       "      <td>52712200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8153</th>\n",
       "      <td>chr3</td>\n",
       "      <td>185807568</td>\n",
       "      <td>185808472</td>\n",
       "      <td>1093.0</td>\n",
       "      <td>1255.0</td>\n",
       "      <td>743.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>185.0</td>\n",
       "      <td>chr3</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8154</th>\n",
       "      <td>chr7</td>\n",
       "      <td>25861697</td>\n",
       "      <td>25863276</td>\n",
       "      <td>1117.0</td>\n",
       "      <td>1121.0</td>\n",
       "      <td>1024.0</td>\n",
       "      <td>open K4me3</td>\n",
       "      <td>3</td>\n",
       "      <td>342.0</td>\n",
       "      <td>chr7</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8155</th>\n",
       "      <td>chr4</td>\n",
       "      <td>74682349</td>\n",
       "      <td>74683776</td>\n",
       "      <td>1122.0</td>\n",
       "      <td>1280.0</td>\n",
       "      <td>683.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>213.0</td>\n",
       "      <td>chr4</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8156 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      chrom      start        end  score_M  score_mG  score_pG            cre  \\\n",
       "0     chr20   10708219   10709212      0.0     323.0       0.0      dist. enh   \n",
       "1     chr20   10670695   10670949      0.0      62.0       0.0      dist. enh   \n",
       "2     chr20   10664319   10665432      0.0     166.0     101.0      dist. enh   \n",
       "3     chr20   10661520   10661815      0.0      86.0       0.0      dist. enh   \n",
       "4     chr20   10660688   10660994      0.0     319.0     159.0      dist. enh   \n",
       "...     ...        ...        ...      ...       ...       ...            ...   \n",
       "8151  chr21   37338463   37339506   1025.0    1068.0    1086.0      just open   \n",
       "8152  chr14   52706170   52707801   1035.0    1044.0    1113.0  promoter-like   \n",
       "8153   chr3  185807568  185808472   1093.0    1255.0     743.0      just open   \n",
       "8154   chr7   25861697   25863276   1117.0    1121.0    1024.0     open K4me3   \n",
       "8155   chr4   74682349   74683776   1122.0    1280.0     683.0      dist. enh   \n",
       "\n",
       "      cre_score  id_index_id chrom_id  ...  name_  start_Rseq_  en_Rseq_  \\\n",
       "0             4        674.0    chr20  ...   None         None      None   \n",
       "1             4        674.0    chr20  ...   None         None      None   \n",
       "2             4        674.0    chr20  ...   None         None      None   \n",
       "3             4        674.0    chr20  ...   None         None      None   \n",
       "4             4        674.0    chr20  ...   None         None      None   \n",
       "...         ...          ...      ...  ...    ...          ...       ...   \n",
       "8151          1        683.0    chr21  ...   None         None      None   \n",
       "8152          6        559.0    chr14  ...  PSMC6     52707200  52728590   \n",
       "8153          1        185.0     chr3  ...   None         None      None   \n",
       "8154          3        342.0     chr7  ...   None         None      None   \n",
       "8155          4        213.0     chr4  ...   None         None      None   \n",
       "\n",
       "       Coverage_      FPKM_        TPM_  TSS_start_  TSS_end_  TSS_start_ext_  \\\n",
       "0           None        NaN        None        <NA>      <NA>             NaN   \n",
       "1           None        NaN        None        <NA>      <NA>             NaN   \n",
       "2           None        NaN        None        <NA>      <NA>             NaN   \n",
       "3           None        NaN        None        <NA>      <NA>             NaN   \n",
       "4           None        NaN        None        <NA>      <NA>             NaN   \n",
       "...          ...        ...         ...         ...       ...             ...   \n",
       "8151        None        NaN        None        <NA>      <NA>             NaN   \n",
       "8152  567.687866  55.392612  117.409393    52707198  52707200      52702198.0   \n",
       "8153        None        NaN        None        <NA>      <NA>             NaN   \n",
       "8154        None        NaN        None        <NA>      <NA>             NaN   \n",
       "8155        None        NaN        None        <NA>      <NA>             NaN   \n",
       "\n",
       "      TSS_end_ext_  \n",
       "0              NaN  \n",
       "1              NaN  \n",
       "2              NaN  \n",
       "3              NaN  \n",
       "4              NaN  \n",
       "...            ...  \n",
       "8151           NaN  \n",
       "8152    52712200.0  \n",
       "8153           NaN  \n",
       "8154           NaN  \n",
       "8155           NaN  \n",
       "\n",
       "[8156 rows x 34 columns]"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cre_genes_c=bf.overlap(id_cre_c,genes,cols2=['chrom','TSS_start','TSS_end'],how='left')\n",
    "\n",
    "cre_genes_c\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "b92e8f3a-feaa-40d3-a2ae-5c11ab0e3571",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5169 2842 5051 5169 2842 5051 2987 2621 2356\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "      <th>cre</th>\n",
       "      <th>cre_score</th>\n",
       "      <th>id_index_id</th>\n",
       "      <th>chrom_id</th>\n",
       "      <th>...</th>\n",
       "      <th>name_</th>\n",
       "      <th>start_Rseq_</th>\n",
       "      <th>en_Rseq_</th>\n",
       "      <th>Coverage_</th>\n",
       "      <th>FPKM_</th>\n",
       "      <th>TPM_</th>\n",
       "      <th>TSS_start_</th>\n",
       "      <th>TSS_end_</th>\n",
       "      <th>TSS_start_ext_</th>\n",
       "      <th>TSS_end_ext_</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr9</td>\n",
       "      <td>112174533</td>\n",
       "      <td>112175583</td>\n",
       "      <td>0.0</td>\n",
       "      <td>291.0</td>\n",
       "      <td>378.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>1295.0</td>\n",
       "      <td>chr9</td>\n",
       "      <td>...</td>\n",
       "      <td>SUSD1</td>\n",
       "      <td>112040783</td>\n",
       "      <td>112175297</td>\n",
       "      <td>170.895981</td>\n",
       "      <td>10.023834</td>\n",
       "      <td>21.246378</td>\n",
       "      <td>112175296</td>\n",
       "      <td>112175298</td>\n",
       "      <td>112170296.0</td>\n",
       "      <td>112180298.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18279312</td>\n",
       "      <td>18279628</td>\n",
       "      <td>0.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18272520</td>\n",
       "      <td>18272764</td>\n",
       "      <td>0.0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr20</td>\n",
       "      <td>18263263</td>\n",
       "      <td>18264156</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1084.0</td>\n",
       "      <td>314.0</td>\n",
       "      <td>ctcf</td>\n",
       "      <td>2</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr9</td>\n",
       "      <td>112360232</td>\n",
       "      <td>112360692</td>\n",
       "      <td>0.0</td>\n",
       "      <td>237.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "      <td>1296.0</td>\n",
       "      <td>chr9</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17055</th>\n",
       "      <td>chr3</td>\n",
       "      <td>185807568</td>\n",
       "      <td>185808472</td>\n",
       "      <td>1093.0</td>\n",
       "      <td>1255.0</td>\n",
       "      <td>743.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>571.0</td>\n",
       "      <td>chr3</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17056</th>\n",
       "      <td>chr21</td>\n",
       "      <td>14382384</td>\n",
       "      <td>14384213</td>\n",
       "      <td>1110.0</td>\n",
       "      <td>1267.0</td>\n",
       "      <td>1212.0</td>\n",
       "      <td>promoter-like</td>\n",
       "      <td>6</td>\n",
       "      <td>2061.0</td>\n",
       "      <td>chr21</td>\n",
       "      <td>...</td>\n",
       "      <td>HSPA13</td>\n",
       "      <td>14371116</td>\n",
       "      <td>14383146</td>\n",
       "      <td>170.593094</td>\n",
       "      <td>9.801558</td>\n",
       "      <td>20.775242</td>\n",
       "      <td>14383145</td>\n",
       "      <td>14383147</td>\n",
       "      <td>14378145.0</td>\n",
       "      <td>14388147.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17057</th>\n",
       "      <td>chr7</td>\n",
       "      <td>25861697</td>\n",
       "      <td>25863276</td>\n",
       "      <td>1117.0</td>\n",
       "      <td>1121.0</td>\n",
       "      <td>1024.0</td>\n",
       "      <td>open K4me3</td>\n",
       "      <td>3</td>\n",
       "      <td>1057.0</td>\n",
       "      <td>chr7</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17058</th>\n",
       "      <td>chr4</td>\n",
       "      <td>74682349</td>\n",
       "      <td>74683776</td>\n",
       "      <td>1122.0</td>\n",
       "      <td>1280.0</td>\n",
       "      <td>683.0</td>\n",
       "      <td>dist. enh</td>\n",
       "      <td>4</td>\n",
       "      <td>645.0</td>\n",
       "      <td>chr4</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17059</th>\n",
       "      <td>chr5</td>\n",
       "      <td>90557902</td>\n",
       "      <td>90559422</td>\n",
       "      <td>1133.0</td>\n",
       "      <td>1270.0</td>\n",
       "      <td>1179.0</td>\n",
       "      <td>promoter-like</td>\n",
       "      <td>6</td>\n",
       "      <td>801.0</td>\n",
       "      <td>chr5</td>\n",
       "      <td>...</td>\n",
       "      <td>ADGRV1</td>\n",
       "      <td>90558797</td>\n",
       "      <td>91164437</td>\n",
       "      <td>23.6957</td>\n",
       "      <td>1.364265</td>\n",
       "      <td>2.891676</td>\n",
       "      <td>90558795</td>\n",
       "      <td>90558797</td>\n",
       "      <td>90553795.0</td>\n",
       "      <td>90563797.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>17060 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom      start        end  score_M  score_mG  score_pG  \\\n",
       "0       chr9  112174533  112175583      0.0     291.0     378.0   \n",
       "1      chr20   18279312   18279628      0.0      65.0       0.0   \n",
       "2      chr20   18272520   18272764      0.0     313.0       0.0   \n",
       "3      chr20   18263263   18264156      0.0    1084.0     314.0   \n",
       "4       chr9  112360232  112360692      0.0     237.0       0.0   \n",
       "...      ...        ...        ...      ...       ...       ...   \n",
       "17055   chr3  185807568  185808472   1093.0    1255.0     743.0   \n",
       "17056  chr21   14382384   14384213   1110.0    1267.0    1212.0   \n",
       "17057   chr7   25861697   25863276   1117.0    1121.0    1024.0   \n",
       "17058   chr4   74682349   74683776   1122.0    1280.0     683.0   \n",
       "17059   chr5   90557902   90559422   1133.0    1270.0    1179.0   \n",
       "\n",
       "                 cre  cre_score  id_index_id chrom_id  ...   name_  \\\n",
       "0          just open          1       1295.0     chr9  ...   SUSD1   \n",
       "1             no cre          0       2045.0    chr20  ...    None   \n",
       "2          just open          1       2045.0    chr20  ...    None   \n",
       "3               ctcf          2       2045.0    chr20  ...    None   \n",
       "4             no cre          0       1296.0     chr9  ...    None   \n",
       "...              ...        ...          ...      ...  ...     ...   \n",
       "17055      just open          1        571.0     chr3  ...    None   \n",
       "17056  promoter-like          6       2061.0    chr21  ...  HSPA13   \n",
       "17057     open K4me3          3       1057.0     chr7  ...    None   \n",
       "17058      dist. enh          4        645.0     chr4  ...    None   \n",
       "17059  promoter-like          6        801.0     chr5  ...  ADGRV1   \n",
       "\n",
       "       start_Rseq_   en_Rseq_   Coverage_      FPKM_       TPM_  TSS_start_  \\\n",
       "0        112040783  112175297  170.895981  10.023834  21.246378   112175296   \n",
       "1             None       None        None        NaN       None        <NA>   \n",
       "2             None       None        None        NaN       None        <NA>   \n",
       "3             None       None        None        NaN       None        <NA>   \n",
       "4             None       None        None        NaN       None        <NA>   \n",
       "...            ...        ...         ...        ...        ...         ...   \n",
       "17055         None       None        None        NaN       None        <NA>   \n",
       "17056     14371116   14383146  170.593094   9.801558  20.775242    14383145   \n",
       "17057         None       None        None        NaN       None        <NA>   \n",
       "17058         None       None        None        NaN       None        <NA>   \n",
       "17059     90558797   91164437     23.6957   1.364265   2.891676    90558795   \n",
       "\n",
       "        TSS_end_  TSS_start_ext_  TSS_end_ext_  \n",
       "0      112175298     112170296.0   112180298.0  \n",
       "1           <NA>             NaN           NaN  \n",
       "2           <NA>             NaN           NaN  \n",
       "3           <NA>             NaN           NaN  \n",
       "4           <NA>             NaN           NaN  \n",
       "...          ...             ...           ...  \n",
       "17055       <NA>             NaN           NaN  \n",
       "17056   14383147      14378145.0    14388147.0  \n",
       "17057       <NA>             NaN           NaN  \n",
       "17058       <NA>             NaN           NaN  \n",
       "17059   90558797      90553795.0    90563797.0  \n",
       "\n",
       "[17060 rows x 34 columns]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "go=cre_genes\n",
    "go_E=go[(go['cre_score']==4)|(go['cre_score']==5)].drop_duplicates(['chrom','start','end'])\n",
    "go_P=go[((go['cre_score']==6)&(go['FPKM_']>0))|(go['FPKM_']>1)].drop_duplicates(['chrom','start','end','TSS_start_'])\n",
    "go_o=go[(go['cre_score']>=1)&(go['cre_score']!=4)&(go['cre_score']!=5)&(go['cre_score']!=6)].drop_duplicates(['chrom','start','end'])\n",
    "\n",
    "g1_E=go_E[go_E['score_mG']>0]\n",
    "g1_P=go_P[go_P['score_mG']>0]\n",
    "g1_o=go_o[go_o['score_mG']>0]\n",
    "bm_E=go_E[(go_E['score_mG']>0)&(go_E['score_M']>0)&(go_E['score_pG']>0)]\n",
    "bm_P=go_P[(go_P['score_mG']>0)&(go_P['score_M']>0)&(go_P['score_pG']>0)]\n",
    "bm_o=go_o[(go_o['score_mG']>0)&(go_o['score_M']>0)&(go_o['score_pG']>0)]\n",
    "print(len(go_E),len(go_P),len(go_o),len(g1_E),len(g1_P),len(g1_o),len(bm_E),len(bm_P),len(bm_o))\n",
    "\n",
    "cre_genes\n",
    "#5169 2842 5051 5169 2842 5051 4192 2768 3263"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "70a9e72c-4b71-4f93-9bfc-eff4b2f8fa4d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3042 1228 1997 3042 1228 1997 1756 1115 902\n",
      "5169 2842 5051 5169 2842 5051 2987 2621 2356\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "      <th>cre</th>\n",
       "      <th>cre_score</th>\n",
       "      <th>id_index_id</th>\n",
       "      <th>chrom_id</th>\n",
       "      <th>...</th>\n",
       "      <th>name_</th>\n",
       "      <th>start_Rseq_</th>\n",
       "      <th>en_Rseq_</th>\n",
       "      <th>Coverage_</th>\n",
       "      <th>FPKM_</th>\n",
       "      <th>TPM_</th>\n",
       "      <th>TSS_start_</th>\n",
       "      <th>TSS_end_</th>\n",
       "      <th>TSS_start_ext_</th>\n",
       "      <th>TSS_end_ext_</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>chr20</td>\n",
       "      <td>10654651</td>\n",
       "      <td>10654929</td>\n",
       "      <td>0.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "      <td>674.0</td>\n",
       "      <td>chr20</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>chr2</td>\n",
       "      <td>239257566</td>\n",
       "      <td>239257804</td>\n",
       "      <td>0.0</td>\n",
       "      <td>211.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>chr2</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>chr2</td>\n",
       "      <td>241336322</td>\n",
       "      <td>241336596</td>\n",
       "      <td>0.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>chr2</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>chr2</td>\n",
       "      <td>240595646</td>\n",
       "      <td>240595944</td>\n",
       "      <td>0.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>chr2</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>chr2</td>\n",
       "      <td>240539934</td>\n",
       "      <td>240540246</td>\n",
       "      <td>0.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no cre</td>\n",
       "      <td>0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>chr2</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8133</th>\n",
       "      <td>chr4</td>\n",
       "      <td>54049701</td>\n",
       "      <td>54051347</td>\n",
       "      <td>926.0</td>\n",
       "      <td>1166.0</td>\n",
       "      <td>797.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>210.0</td>\n",
       "      <td>chr4</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8147</th>\n",
       "      <td>chr12</td>\n",
       "      <td>124904435</td>\n",
       "      <td>124905118</td>\n",
       "      <td>969.0</td>\n",
       "      <td>914.0</td>\n",
       "      <td>733.0</td>\n",
       "      <td>ctcf</td>\n",
       "      <td>2</td>\n",
       "      <td>526.0</td>\n",
       "      <td>chr12</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8151</th>\n",
       "      <td>chr21</td>\n",
       "      <td>37338463</td>\n",
       "      <td>37339506</td>\n",
       "      <td>1025.0</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>1086.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>683.0</td>\n",
       "      <td>chr21</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8153</th>\n",
       "      <td>chr3</td>\n",
       "      <td>185807568</td>\n",
       "      <td>185808472</td>\n",
       "      <td>1093.0</td>\n",
       "      <td>1255.0</td>\n",
       "      <td>743.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>185.0</td>\n",
       "      <td>chr3</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8154</th>\n",
       "      <td>chr7</td>\n",
       "      <td>25861697</td>\n",
       "      <td>25863276</td>\n",
       "      <td>1117.0</td>\n",
       "      <td>1121.0</td>\n",
       "      <td>1024.0</td>\n",
       "      <td>open K4me3</td>\n",
       "      <td>3</td>\n",
       "      <td>342.0</td>\n",
       "      <td>chr7</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3325 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      chrom      start        end  score_M  score_mG  score_pG         cre  \\\n",
       "5     chr20   10654651   10654929      0.0     176.0       0.0      no cre   \n",
       "9      chr2  239257566  239257804      0.0     211.0       0.0      no cre   \n",
       "10     chr2  241336322  241336596      0.0      80.0       0.0      no cre   \n",
       "11     chr2  240595646  240595944      0.0      48.0       0.0      no cre   \n",
       "13     chr2  240539934  240540246      0.0     172.0       0.0      no cre   \n",
       "...     ...        ...        ...      ...       ...       ...         ...   \n",
       "8133   chr4   54049701   54051347    926.0    1166.0     797.0   just open   \n",
       "8147  chr12  124904435  124905118    969.0     914.0     733.0        ctcf   \n",
       "8151  chr21   37338463   37339506   1025.0    1068.0    1086.0   just open   \n",
       "8153   chr3  185807568  185808472   1093.0    1255.0     743.0   just open   \n",
       "8154   chr7   25861697   25863276   1117.0    1121.0    1024.0  open K4me3   \n",
       "\n",
       "      cre_score  id_index_id chrom_id  ...  name_  start_Rseq_  en_Rseq_  \\\n",
       "5             0        674.0    chr20  ...   None         None      None   \n",
       "9             0        141.0     chr2  ...   None         None      None   \n",
       "10            0        143.0     chr2  ...   None         None      None   \n",
       "11            0        142.0     chr2  ...   None         None      None   \n",
       "13            0        142.0     chr2  ...   None         None      None   \n",
       "...         ...          ...      ...  ...    ...          ...       ...   \n",
       "8133          1        210.0     chr4  ...   None         None      None   \n",
       "8147          2        526.0    chr12  ...   None         None      None   \n",
       "8151          1        683.0    chr21  ...   None         None      None   \n",
       "8153          1        185.0     chr3  ...   None         None      None   \n",
       "8154          3        342.0     chr7  ...   None         None      None   \n",
       "\n",
       "      Coverage_  FPKM_  TPM_  TSS_start_  TSS_end_  TSS_start_ext_  \\\n",
       "5          None    NaN  None        <NA>      <NA>             NaN   \n",
       "9          None    NaN  None        <NA>      <NA>             NaN   \n",
       "10         None    NaN  None        <NA>      <NA>             NaN   \n",
       "11         None    NaN  None        <NA>      <NA>             NaN   \n",
       "13         None    NaN  None        <NA>      <NA>             NaN   \n",
       "...         ...    ...   ...         ...       ...             ...   \n",
       "8133       None    NaN  None        <NA>      <NA>             NaN   \n",
       "8147       None    NaN  None        <NA>      <NA>             NaN   \n",
       "8151       None    NaN  None        <NA>      <NA>             NaN   \n",
       "8153       None    NaN  None        <NA>      <NA>             NaN   \n",
       "8154       None    NaN  None        <NA>      <NA>             NaN   \n",
       "\n",
       "      TSS_end_ext_  \n",
       "5              NaN  \n",
       "9              NaN  \n",
       "10             NaN  \n",
       "11             NaN  \n",
       "13             NaN  \n",
       "...            ...  \n",
       "8133           NaN  \n",
       "8147           NaN  \n",
       "8151           NaN  \n",
       "8153           NaN  \n",
       "8154           NaN  \n",
       "\n",
       "[3325 rows x 34 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "goc=cre_genes_c\n",
    "goc_E=goc[(goc['cre_score']==4)|(goc['cre_score']==5)].drop_duplicates(['chrom','start','end'])\n",
    "goc_P=goc[((goc['cre_score']==6)&(goc['FPKM_']>0))|(goc['FPKM_']>1)].drop_duplicates(['chrom','start','end','TSS_start_'])\n",
    "goc_o=goc[(goc['cre_score']>=1)&(goc['cre_score']!=4)&(goc['cre_score']!=5)&(goc['cre_score']!=6)].drop_duplicates(['chrom','start','end'])\n",
    "goc_no=goc[(goc['cre_score']>=0)&(goc['cre_score']!=4)&(goc['cre_score']!=5)&(goc['cre_score']!=6)].drop_duplicates(['chrom','start','end'])\n",
    "\n",
    "g1_E_c=goc_E[goc_E['score_mG']>0]\n",
    "g1_P_c=goc_P[goc_P['score_mG']>0]\n",
    "g1_o_c=goc_o[goc_o['score_mG']>0]\n",
    "bm_E_c=goc_E[(goc_E['score_mG']>0)&(goc_E['score_M']>0)&(goc_E['score_pG']>0)]\n",
    "bm_P_c=goc_P[(goc_P['score_mG']>0)&(goc_P['score_M']>0)&(goc_P['score_pG']>0)]\n",
    "bm_o_c=goc_o[(goc_o['score_mG']>0)&(goc_o['score_M']>0)&(goc_o['score_pG']>0)]\n",
    "print(len(goc_E),len(goc_P),len(goc_o),len(g1_E_c),len(g1_P_c),len(g1_o_c),len(bm_E_c),len(bm_P_c),len(bm_o_c))\n",
    "print(len(go_E),len(go_P),len(go_o),len(g1_E),len(g1_P),len(g1_o),len(bm_E),len(bm_P),len(bm_o))\n",
    "# 3042 1228 1997 3042 1228 1997 1756 1115 902\n",
    "# 5169 2842 5051 5169 2842 5051 2987 2621 2356\n",
    "goc_no\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "78153b0e-cc8f-4f80-8841-d01306f4e4e8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_193306/3901843386.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  bm_E['bm_enh'] = bm_E.groupby('id_index_id')['id_index_id'].transform('count')\n",
      "/tmp/ipykernel_193306/3901843386.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  bm_P['bm_onTSS'] = bm_P.groupby('id_index_id')['id_index_id'].transform('count')\n",
      "/tmp/ipykernel_193306/3901843386.py:7: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  bm_o['bm_other'] = bm_o.groupby('id_index_id')['id_index_id'].transform('count')\n",
      "/tmp/ipykernel_193306/3901843386.py:12: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  bm_E_c['bm_enh'] = bm_E_c.groupby('id_index_id')['id_index_id'].transform('count')\n",
      "/tmp/ipykernel_193306/3901843386.py:15: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  bm_P_c['bm_onTSS'] = bm_P_c.groupby('id_index_id')['id_index_id'].transform('count')\n",
      "/tmp/ipykernel_193306/3901843386.py:18: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  bm_o_c['bm_other'] = bm_o_c.groupby('id_index_id')['id_index_id'].transform('count')\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>score_M</th>\n",
       "      <th>score_mG</th>\n",
       "      <th>score_pG</th>\n",
       "      <th>cre</th>\n",
       "      <th>cre_score</th>\n",
       "      <th>id_index_id</th>\n",
       "      <th>chrom_id</th>\n",
       "      <th>...</th>\n",
       "      <th>start_Rseq_</th>\n",
       "      <th>en_Rseq_</th>\n",
       "      <th>Coverage_</th>\n",
       "      <th>FPKM_</th>\n",
       "      <th>TPM_</th>\n",
       "      <th>TSS_start_</th>\n",
       "      <th>TSS_end_</th>\n",
       "      <th>TSS_start_ext_</th>\n",
       "      <th>TSS_end_ext_</th>\n",
       "      <th>bm_other</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3493</th>\n",
       "      <td>chr22</td>\n",
       "      <td>39529180</td>\n",
       "      <td>39529509</td>\n",
       "      <td>41.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>ctcf</td>\n",
       "      <td>2</td>\n",
       "      <td>692.0</td>\n",
       "      <td>chr22</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3497</th>\n",
       "      <td>chr9</td>\n",
       "      <td>137195441</td>\n",
       "      <td>137195955</td>\n",
       "      <td>43.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>ctcf</td>\n",
       "      <td>2</td>\n",
       "      <td>403.0</td>\n",
       "      <td>chr9</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3511</th>\n",
       "      <td>chr17</td>\n",
       "      <td>2043745</td>\n",
       "      <td>2044166</td>\n",
       "      <td>54.0</td>\n",
       "      <td>171.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>599.0</td>\n",
       "      <td>chr17</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3517</th>\n",
       "      <td>chr17</td>\n",
       "      <td>83079402</td>\n",
       "      <td>83079708</td>\n",
       "      <td>56.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>634.0</td>\n",
       "      <td>chr17</td>\n",
       "      <td>...</td>\n",
       "      <td>83079609</td>\n",
       "      <td>83095126</td>\n",
       "      <td>21.213465</td>\n",
       "      <td>3.927635</td>\n",
       "      <td>8.32496</td>\n",
       "      <td>83079607</td>\n",
       "      <td>83079609</td>\n",
       "      <td>83074607.0</td>\n",
       "      <td>83084609.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3518</th>\n",
       "      <td>chr11</td>\n",
       "      <td>2210728</td>\n",
       "      <td>2211705</td>\n",
       "      <td>56.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>ctcf</td>\n",
       "      <td>2</td>\n",
       "      <td>442.0</td>\n",
       "      <td>chr11</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8133</th>\n",
       "      <td>chr4</td>\n",
       "      <td>54049701</td>\n",
       "      <td>54051347</td>\n",
       "      <td>926.0</td>\n",
       "      <td>1166.0</td>\n",
       "      <td>797.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>210.0</td>\n",
       "      <td>chr4</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8147</th>\n",
       "      <td>chr12</td>\n",
       "      <td>124904435</td>\n",
       "      <td>124905118</td>\n",
       "      <td>969.0</td>\n",
       "      <td>914.0</td>\n",
       "      <td>733.0</td>\n",
       "      <td>ctcf</td>\n",
       "      <td>2</td>\n",
       "      <td>526.0</td>\n",
       "      <td>chr12</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8151</th>\n",
       "      <td>chr21</td>\n",
       "      <td>37338463</td>\n",
       "      <td>37339506</td>\n",
       "      <td>1025.0</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>1086.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>683.0</td>\n",
       "      <td>chr21</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8153</th>\n",
       "      <td>chr3</td>\n",
       "      <td>185807568</td>\n",
       "      <td>185808472</td>\n",
       "      <td>1093.0</td>\n",
       "      <td>1255.0</td>\n",
       "      <td>743.0</td>\n",
       "      <td>just open</td>\n",
       "      <td>1</td>\n",
       "      <td>185.0</td>\n",
       "      <td>chr3</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8154</th>\n",
       "      <td>chr7</td>\n",
       "      <td>25861697</td>\n",
       "      <td>25863276</td>\n",
       "      <td>1117.0</td>\n",
       "      <td>1121.0</td>\n",
       "      <td>1024.0</td>\n",
       "      <td>open K4me3</td>\n",
       "      <td>3</td>\n",
       "      <td>342.0</td>\n",
       "      <td>chr7</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>902 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      chrom      start        end  score_M  score_mG  score_pG         cre  \\\n",
       "3493  chr22   39529180   39529509     41.0      92.0     139.0        ctcf   \n",
       "3497   chr9  137195441  137195955     43.0     129.0      45.0        ctcf   \n",
       "3511  chr17    2043745    2044166     54.0     171.0      77.0   just open   \n",
       "3517  chr17   83079402   83079708     56.0      86.0     126.0   just open   \n",
       "3518  chr11    2210728    2211705     56.0     190.0     140.0        ctcf   \n",
       "...     ...        ...        ...      ...       ...       ...         ...   \n",
       "8133   chr4   54049701   54051347    926.0    1166.0     797.0   just open   \n",
       "8147  chr12  124904435  124905118    969.0     914.0     733.0        ctcf   \n",
       "8151  chr21   37338463   37339506   1025.0    1068.0    1086.0   just open   \n",
       "8153   chr3  185807568  185808472   1093.0    1255.0     743.0   just open   \n",
       "8154   chr7   25861697   25863276   1117.0    1121.0    1024.0  open K4me3   \n",
       "\n",
       "      cre_score  id_index_id chrom_id  ...  start_Rseq_  en_Rseq_  Coverage_  \\\n",
       "3493          2        692.0    chr22  ...         None      None       None   \n",
       "3497          2        403.0     chr9  ...         None      None       None   \n",
       "3511          1        599.0    chr17  ...         None      None       None   \n",
       "3517          1        634.0    chr17  ...     83079609  83095126  21.213465   \n",
       "3518          2        442.0    chr11  ...         None      None       None   \n",
       "...         ...          ...      ...  ...          ...       ...        ...   \n",
       "8133          1        210.0     chr4  ...         None      None       None   \n",
       "8147          2        526.0    chr12  ...         None      None       None   \n",
       "8151          1        683.0    chr21  ...         None      None       None   \n",
       "8153          1        185.0     chr3  ...         None      None       None   \n",
       "8154          3        342.0     chr7  ...         None      None       None   \n",
       "\n",
       "         FPKM_     TPM_  TSS_start_  TSS_end_  TSS_start_ext_  TSS_end_ext_  \\\n",
       "3493       NaN     None        <NA>      <NA>             NaN           NaN   \n",
       "3497       NaN     None        <NA>      <NA>             NaN           NaN   \n",
       "3511       NaN     None        <NA>      <NA>             NaN           NaN   \n",
       "3517  3.927635  8.32496    83079607  83079609      83074607.0    83084609.0   \n",
       "3518       NaN     None        <NA>      <NA>             NaN           NaN   \n",
       "...        ...      ...         ...       ...             ...           ...   \n",
       "8133       NaN     None        <NA>      <NA>             NaN           NaN   \n",
       "8147       NaN     None        <NA>      <NA>             NaN           NaN   \n",
       "8151       NaN     None        <NA>      <NA>             NaN           NaN   \n",
       "8153       NaN     None        <NA>      <NA>             NaN           NaN   \n",
       "8154       NaN     None        <NA>      <NA>             NaN           NaN   \n",
       "\n",
       "      bm_other  \n",
       "3493         1  \n",
       "3497         1  \n",
       "3511         3  \n",
       "3517         3  \n",
       "3518         3  \n",
       "...        ...  \n",
       "8133         2  \n",
       "8147         2  \n",
       "8151         1  \n",
       "8153         1  \n",
       "8154         4  \n",
       "\n",
       "[902 rows x 35 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bm_E['bm_enh'] = bm_E.groupby('id_index_id')['id_index_id'].transform('count')\n",
    "g1_E['g1_enh'] = g1_E.groupby('id_index_id')['id_index_id'].transform('count')\n",
    "\n",
    "bm_P['bm_onTSS'] = bm_P.groupby('id_index_id')['id_index_id'].transform('count')\n",
    "g1_P['g1_onTSS'] = g1_P.groupby('id_index_id')['id_index_id'].transform('count')\n",
    "\n",
    "bm_o['bm_other'] = bm_o.groupby('id_index_id')['id_index_id'].transform('count')\n",
    "g1_o['g1_other'] = g1_o.groupby('id_index_id')['id_index_id'].transform('count')\n",
    "\n",
    "\n",
    "\n",
    "bm_E_c['bm_enh'] = bm_E_c.groupby('id_index_id')['id_index_id'].transform('count')\n",
    "g1_E_c['g1_enh'] = g1_E_c.groupby('id_index_id')['id_index_id'].transform('count')\n",
    "\n",
    "bm_P_c['bm_onTSS'] = bm_P_c.groupby('id_index_id')['id_index_id'].transform('count')\n",
    "g1_P_c['g1_onTSS'] = g1_P_c.groupby('id_index_id')['id_index_id'].transform('count')\n",
    "\n",
    "bm_o_c['bm_other'] = bm_o_c.groupby('id_index_id')['id_index_id'].transform('count')\n",
    "g1_o_c['g1_other'] = g1_o_c.groupby('id_index_id')['id_index_id'].transform('count')\n",
    "\n",
    "bm_o_c\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "88a6d191-517a-4b16-b198-0bbc3e6cfc59",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1239 1521 1687 1047 1448 1260 507 521 592 455 494 444\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id_index_id</th>\n",
       "      <th>g1_other</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1973</th>\n",
       "      <td>693.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1976</th>\n",
       "      <td>694.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981</th>\n",
       "      <td>695.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>696.0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>697.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>592 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id_index_id  g1_other\n",
       "0             0.0         2\n",
       "2             1.0         3\n",
       "5             2.0         3\n",
       "8             3.0         4\n",
       "12            4.0         2\n",
       "...           ...       ...\n",
       "1973        693.0         3\n",
       "1976        694.0         5\n",
       "1981        695.0         4\n",
       "1985        696.0         8\n",
       "1993        697.0         4\n",
       "\n",
       "[592 rows x 2 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bm_E=bm_E[['id_index_id','bm_enh']].sort_values('id_index_id').reset_index(drop=True).drop_duplicates()\n",
    "bm_P=bm_P[['id_index_id','bm_onTSS']].sort_values('id_index_id').reset_index(drop=True).drop_duplicates()\n",
    "bm_o=bm_o[['id_index_id','bm_other']].sort_values('id_index_id').reset_index(drop=True).drop_duplicates()\n",
    "\n",
    "g1_E=g1_E[['id_index_id','g1_enh']].sort_values('id_index_id').reset_index(drop=True).drop_duplicates()\n",
    "g1_P=g1_P[['id_index_id','g1_onTSS']].sort_values('id_index_id').reset_index(drop=True).drop_duplicates()\n",
    "g1_o=g1_o[['id_index_id','g1_other']].sort_values('id_index_id').reset_index(drop=True).drop_duplicates()\n",
    "\n",
    "bm_E_c=bm_E_c[['id_index_id','bm_enh']].sort_values('id_index_id').reset_index(drop=True).drop_duplicates()\n",
    "bm_P_c=bm_P_c[['id_index_id','bm_onTSS']].sort_values('id_index_id').reset_index(drop=True).drop_duplicates()\n",
    "bm_o_c=bm_o_c[['id_index_id','bm_other']].sort_values('id_index_id').reset_index(drop=True).drop_duplicates()\n",
    "\n",
    "g1_E_c=g1_E_c[['id_index_id','g1_enh']].sort_values('id_index_id').reset_index(drop=True).drop_duplicates()\n",
    "g1_P_c=g1_P_c[['id_index_id','g1_onTSS']].sort_values('id_index_id').reset_index(drop=True).drop_duplicates()\n",
    "g1_o_c=g1_o_c[['id_index_id','g1_other']].sort_values('id_index_id').reset_index(drop=True).drop_duplicates()\n",
    "\n",
    "print(len(g1_E),len(g1_P),len(g1_o),len(bm_E),len(bm_P),len(bm_o),len(g1_E_c),len(g1_P_c),len(g1_o_c),len(bm_E_c),len(bm_P_c),len(bm_o_c))\n",
    "g1_o_c\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "f0dfe3df-c9fc-4019-a985-6084147e8f7f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_193306/4234334618.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  IDs['id_index_id']=IDs['id_index']\n",
      "/tmp/ipykernel_193306/4234334618.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  IDs_c['id_index_id']=IDs_c['id_index']\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id_index</th>\n",
       "      <th>chrom</th>\n",
       "      <th>peak_start_ext</th>\n",
       "      <th>peak_end_ext</th>\n",
       "      <th>id_index_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>chr1</td>\n",
       "      <td>1005000</td>\n",
       "      <td>1045000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>chr1</td>\n",
       "      <td>1885000</td>\n",
       "      <td>1925000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>chr1</td>\n",
       "      <td>7975000</td>\n",
       "      <td>8025000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>chr1</td>\n",
       "      <td>16115000</td>\n",
       "      <td>16195000</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>chr1</td>\n",
       "      <td>28495000</td>\n",
       "      <td>28555000</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>693</th>\n",
       "      <td>693</td>\n",
       "      <td>chr22</td>\n",
       "      <td>45135000</td>\n",
       "      <td>45195000</td>\n",
       "      <td>693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>694</th>\n",
       "      <td>694</td>\n",
       "      <td>chr22</td>\n",
       "      <td>46015000</td>\n",
       "      <td>46155000</td>\n",
       "      <td>694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>695</th>\n",
       "      <td>695</td>\n",
       "      <td>chr22</td>\n",
       "      <td>46735000</td>\n",
       "      <td>46775000</td>\n",
       "      <td>695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>696</th>\n",
       "      <td>696</td>\n",
       "      <td>chr22</td>\n",
       "      <td>49915000</td>\n",
       "      <td>49995000</td>\n",
       "      <td>696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>697</th>\n",
       "      <td>697</td>\n",
       "      <td>chr22</td>\n",
       "      <td>50255000</td>\n",
       "      <td>50325000</td>\n",
       "      <td>697</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>698 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     id_index  chrom  peak_start_ext  peak_end_ext  id_index_id\n",
       "0           0   chr1         1005000       1045000            0\n",
       "1           1   chr1         1885000       1925000            1\n",
       "2           2   chr1         7975000       8025000            2\n",
       "3           3   chr1        16115000      16195000            3\n",
       "4           4   chr1        28495000      28555000            4\n",
       "..        ...    ...             ...           ...          ...\n",
       "693       693  chr22        45135000      45195000          693\n",
       "694       694  chr22        46015000      46155000          694\n",
       "695       695  chr22        46735000      46775000          695\n",
       "696       696  chr22        49915000      49995000          696\n",
       "697       697  chr22        50255000      50325000          697\n",
       "\n",
       "[698 rows x 5 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IDs=IDa[['id_index','chrom','peak_start_ext','peak_end_ext']]\n",
    "IDs['id_index_id']=IDs['id_index']\n",
    "\n",
    "IDs_c=IDc[['id_index','chrom','peak_start_ext','peak_end_ext']]\n",
    "IDs_c['id_index_id']=IDs_c['id_index']\n",
    "IDs_c\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "394b15ea-85ae-483c-a1b1-ec80528ef885",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id_index</th>\n",
       "      <th>chrom</th>\n",
       "      <th>peak_start_ext</th>\n",
       "      <th>peak_end_ext</th>\n",
       "      <th>id_index_id</th>\n",
       "      <th>g1_enh</th>\n",
       "      <th>g1_onTSS</th>\n",
       "      <th>bm_enh</th>\n",
       "      <th>bm_onTSS</th>\n",
       "      <th>g1_other</th>\n",
       "      <th>bm_other</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>chr1</td>\n",
       "      <td>1005000</td>\n",
       "      <td>1045000</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>chr1</td>\n",
       "      <td>1885000</td>\n",
       "      <td>1925000</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>chr1</td>\n",
       "      <td>6585000</td>\n",
       "      <td>6625000</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>chr1</td>\n",
       "      <td>7755000</td>\n",
       "      <td>7795000</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>chr1</td>\n",
       "      <td>7975000</td>\n",
       "      <td>8025000</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2100</th>\n",
       "      <td>2100</td>\n",
       "      <td>chr22</td>\n",
       "      <td>45135000</td>\n",
       "      <td>45195000</td>\n",
       "      <td>2100</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2101</th>\n",
       "      <td>2101</td>\n",
       "      <td>chr22</td>\n",
       "      <td>46015000</td>\n",
       "      <td>46155000</td>\n",
       "      <td>2101</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2102</th>\n",
       "      <td>2102</td>\n",
       "      <td>chr22</td>\n",
       "      <td>46735000</td>\n",
       "      <td>46775000</td>\n",
       "      <td>2102</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2103</th>\n",
       "      <td>2103</td>\n",
       "      <td>chr22</td>\n",
       "      <td>49915000</td>\n",
       "      <td>49995000</td>\n",
       "      <td>2103</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2104</th>\n",
       "      <td>2104</td>\n",
       "      <td>chr22</td>\n",
       "      <td>50255000</td>\n",
       "      <td>50325000</td>\n",
       "      <td>2104</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2105 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id_index  chrom  peak_start_ext  peak_end_ext  id_index_id  g1_enh  \\\n",
       "0            0   chr1         1005000       1045000            0     4.0   \n",
       "1            1   chr1         1885000       1925000            1     1.0   \n",
       "2            2   chr1         6585000       6625000            2     NaN   \n",
       "3            3   chr1         7755000       7795000            3     NaN   \n",
       "4            4   chr1         7975000       8025000            4     4.0   \n",
       "...        ...    ...             ...           ...          ...     ...   \n",
       "2100      2100  chr22        45135000      45195000         2100     2.0   \n",
       "2101      2101  chr22        46015000      46155000         2101    19.0   \n",
       "2102      2102  chr22        46735000      46775000         2102     2.0   \n",
       "2103      2103  chr22        49915000      49995000         2103     5.0   \n",
       "2104      2104  chr22        50255000      50325000         2104     2.0   \n",
       "\n",
       "      g1_onTSS  bm_enh  bm_onTSS  g1_other  bm_other  \n",
       "0          2.0     1.0       2.0       2.0       NaN  \n",
       "1          2.0     1.0       2.0       3.0       1.0  \n",
       "2          3.0     NaN       2.0       1.0       NaN  \n",
       "3          2.0     NaN       2.0       NaN       NaN  \n",
       "4          NaN     2.0       NaN       3.0       1.0  \n",
       "...        ...     ...       ...       ...       ...  \n",
       "2100       2.0     NaN       2.0       3.0       1.0  \n",
       "2101       4.0     7.0       4.0       5.0       3.0  \n",
       "2102       2.0     2.0       2.0       4.0       1.0  \n",
       "2103       3.0     3.0       3.0       8.0       3.0  \n",
       "2104       2.0     2.0       2.0       4.0       1.0  \n",
       "\n",
       "[2105 rows x 11 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id_freq2=(((IDs.merge(g1_E,on='id_index_id',how='outer')).merge(g1_P,on='id_index_id',how='outer')).merge(bm_E,on='id_index_id',how='outer')).merge(bm_P,on='id_index_id',how='outer')\n",
    "id_freq=(id_freq2.merge(g1_o,on='id_index_id',how='outer')).merge(bm_o,on='id_index_id',how='outer')\n",
    "id_freq_g1notss=id_freq[id_freq['g1_onTSS'].isnull()]\n",
    "id_freq_bmnotss=id_freq[id_freq['bm_onTSS'].isnull()]\n",
    "\n",
    "id_freqc2=(((IDs_c.merge(g1_E_c,on='id_index_id',how='outer')).merge(g1_P_c,on='id_index_id',how='outer')).merge(bm_E_c,on='id_index_id',how='outer')).merge(bm_P_c,on='id_index_id',how='outer')\n",
    "id_freqc=(id_freqc2.merge(g1_o_c,on='id_index_id',how='outer')).merge(bm_o_c,on='id_index_id',how='outer')\n",
    "id_freqc_g1notss=id_freqc[id_freqc['g1_onTSS'].isnull()]\n",
    "id_freqc_bmnotss=id_freqc[id_freqc['bm_onTSS'].isnull()]\n",
    "\n",
    "id_freq\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18c7d349-2e0b-423e-992f-e32082478d38",
   "metadata": {},
   "source": [
    "# scatter\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "59aa9c90-7830-4698-bbc2-e11ca721f090",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id_index</th>\n",
       "      <th>chrom</th>\n",
       "      <th>peak_start_ext</th>\n",
       "      <th>peak_end_ext</th>\n",
       "      <th>id_index_id</th>\n",
       "      <th>g1_enh</th>\n",
       "      <th>g1_onTSS</th>\n",
       "      <th>bm_enh</th>\n",
       "      <th>bm_onTSS</th>\n",
       "      <th>g1_other</th>\n",
       "      <th>bm_other</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>chr1</td>\n",
       "      <td>1005000</td>\n",
       "      <td>1045000</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>chr1</td>\n",
       "      <td>1885000</td>\n",
       "      <td>1925000</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>chr1</td>\n",
       "      <td>6585000</td>\n",
       "      <td>6625000</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>chr1</td>\n",
       "      <td>7755000</td>\n",
       "      <td>7795000</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>chr1</td>\n",
       "      <td>7975000</td>\n",
       "      <td>8025000</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2100</th>\n",
       "      <td>2100</td>\n",
       "      <td>chr22</td>\n",
       "      <td>45135000</td>\n",
       "      <td>45195000</td>\n",
       "      <td>2100</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2101</th>\n",
       "      <td>2101</td>\n",
       "      <td>chr22</td>\n",
       "      <td>46015000</td>\n",
       "      <td>46155000</td>\n",
       "      <td>2101</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2102</th>\n",
       "      <td>2102</td>\n",
       "      <td>chr22</td>\n",
       "      <td>46735000</td>\n",
       "      <td>46775000</td>\n",
       "      <td>2102</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2103</th>\n",
       "      <td>2103</td>\n",
       "      <td>chr22</td>\n",
       "      <td>49915000</td>\n",
       "      <td>49995000</td>\n",
       "      <td>2103</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2104</th>\n",
       "      <td>2104</td>\n",
       "      <td>chr22</td>\n",
       "      <td>50255000</td>\n",
       "      <td>50325000</td>\n",
       "      <td>2104</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2105 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id_index  chrom  peak_start_ext  peak_end_ext  id_index_id  g1_enh  \\\n",
       "0            0   chr1         1005000       1045000            0     4.0   \n",
       "1            1   chr1         1885000       1925000            1     1.0   \n",
       "2            2   chr1         6585000       6625000            2     NaN   \n",
       "3            3   chr1         7755000       7795000            3     NaN   \n",
       "4            4   chr1         7975000       8025000            4     4.0   \n",
       "...        ...    ...             ...           ...          ...     ...   \n",
       "2100      2100  chr22        45135000      45195000         2100     2.0   \n",
       "2101      2101  chr22        46015000      46155000         2101    19.0   \n",
       "2102      2102  chr22        46735000      46775000         2102     2.0   \n",
       "2103      2103  chr22        49915000      49995000         2103     5.0   \n",
       "2104      2104  chr22        50255000      50325000         2104     2.0   \n",
       "\n",
       "      g1_onTSS  bm_enh  bm_onTSS  g1_other  bm_other  \n",
       "0          2.0     1.0       2.0       2.0       NaN  \n",
       "1          2.0     1.0       2.0       3.0       1.0  \n",
       "2          3.0     NaN       2.0       1.0       NaN  \n",
       "3          2.0     NaN       2.0       NaN       NaN  \n",
       "4          NaN     2.0       NaN       3.0       1.0  \n",
       "...        ...     ...       ...       ...       ...  \n",
       "2100       2.0     NaN       2.0       3.0       1.0  \n",
       "2101       4.0     7.0       4.0       5.0       3.0  \n",
       "2102       2.0     2.0       2.0       4.0       1.0  \n",
       "2103       3.0     3.0       3.0       8.0       3.0  \n",
       "2104       2.0     2.0       2.0       4.0       1.0  \n",
       "\n",
       "[2105 rows x 11 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id_freq2=(((IDs.merge(g1_E,on='id_index_id',how='outer')).merge(g1_P,on='id_index_id',how='outer')).merge(bm_E,on='id_index_id',how='outer')).merge(bm_P,on='id_index_id',how='outer')\n",
    "id_freq=(id_freq2.merge(g1_o,on='id_index_id',how='outer')).merge(bm_o,on='id_index_id',how='outer')\n",
    "\n",
    "id_freqc2=(((IDs_c.merge(g1_E_c,on='id_index_id',how='outer')).merge(g1_P_c,on='id_index_id',how='outer')).merge(bm_E_c,on='id_index_id',how='outer')).merge(bm_P_c,on='id_index_id',how='outer')\n",
    "id_freqc=(id_freqc2.merge(g1_o_c,on='id_index_id',how='outer')).merge(bm_o_c,on='id_index_id',how='outer')\n",
    "\n",
    "\n",
    "id_freq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "d8993984-82ce-45af-b737-c34695a4a810",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id_index</th>\n",
       "      <th>chrom</th>\n",
       "      <th>peak_start_ext</th>\n",
       "      <th>peak_end_ext</th>\n",
       "      <th>id_index_id</th>\n",
       "      <th>g1_enh</th>\n",
       "      <th>g1_onTSS</th>\n",
       "      <th>bm_enh</th>\n",
       "      <th>bm_onTSS</th>\n",
       "      <th>g1_other</th>\n",
       "      <th>bm_other</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>chr1</td>\n",
       "      <td>1005000</td>\n",
       "      <td>1045000</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>chr1</td>\n",
       "      <td>1885000</td>\n",
       "      <td>1925000</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>chr1</td>\n",
       "      <td>6585000</td>\n",
       "      <td>6625000</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>chr1</td>\n",
       "      <td>7755000</td>\n",
       "      <td>7795000</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>chr1</td>\n",
       "      <td>7975000</td>\n",
       "      <td>8025000</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2100</th>\n",
       "      <td>2100</td>\n",
       "      <td>chr22</td>\n",
       "      <td>45135000</td>\n",
       "      <td>45195000</td>\n",
       "      <td>2100</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2101</th>\n",
       "      <td>2101</td>\n",
       "      <td>chr22</td>\n",
       "      <td>46015000</td>\n",
       "      <td>46155000</td>\n",
       "      <td>2101</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2102</th>\n",
       "      <td>2102</td>\n",
       "      <td>chr22</td>\n",
       "      <td>46735000</td>\n",
       "      <td>46775000</td>\n",
       "      <td>2102</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2103</th>\n",
       "      <td>2103</td>\n",
       "      <td>chr22</td>\n",
       "      <td>49915000</td>\n",
       "      <td>49995000</td>\n",
       "      <td>2103</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>8.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2104</th>\n",
       "      <td>2104</td>\n",
       "      <td>chr22</td>\n",
       "      <td>50255000</td>\n",
       "      <td>50325000</td>\n",
       "      <td>2104</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2105 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id_index  chrom  peak_start_ext  peak_end_ext  id_index_id  g1_enh  \\\n",
       "0            0   chr1         1005000       1045000            0     4.0   \n",
       "1            1   chr1         1885000       1925000            1     1.0   \n",
       "2            2   chr1         6585000       6625000            2     0.0   \n",
       "3            3   chr1         7755000       7795000            3     0.0   \n",
       "4            4   chr1         7975000       8025000            4     4.0   \n",
       "...        ...    ...             ...           ...          ...     ...   \n",
       "2100      2100  chr22        45135000      45195000         2100     2.0   \n",
       "2101      2101  chr22        46015000      46155000         2101    19.0   \n",
       "2102      2102  chr22        46735000      46775000         2102     2.0   \n",
       "2103      2103  chr22        49915000      49995000         2103     5.0   \n",
       "2104      2104  chr22        50255000      50325000         2104     2.0   \n",
       "\n",
       "      g1_onTSS  bm_enh  bm_onTSS  g1_other  bm_other  \n",
       "0          2.0       1         2       2.0       0.0  \n",
       "1          2.0       1         2       3.0       1.0  \n",
       "2          3.0       0         2       1.0       0.0  \n",
       "3          2.0       0         2       0.0       0.0  \n",
       "4          0.0       2         0       3.0       1.0  \n",
       "...        ...     ...       ...       ...       ...  \n",
       "2100       2.0       0         2       3.0       1.0  \n",
       "2101       4.0       7         4       5.0       3.0  \n",
       "2102       2.0       2         2       4.0       1.0  \n",
       "2103       3.0       3         3       8.0       3.0  \n",
       "2104       2.0       2         2       4.0       1.0  \n",
       "\n",
       "[2105 rows x 11 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id_freq.fillna(0, inplace=True)\n",
    "id_freq['bm_enh']=id_freq['bm_enh'].astype(int)\n",
    "id_freq['bm_onTSS']=id_freq['bm_onTSS'].astype(int)\n",
    "\n",
    "id_freqc.fillna(0, inplace=True)\n",
    "id_freqc['bm_enh']=id_freqc['bm_enh'].astype(int)\n",
    "id_freqc['bm_onTSS']=id_freqc['bm_onTSS'].astype(int)\n",
    "\n",
    "id_freq\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "b37cce16-31c6-4977-aa37-144474c73a0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>p</th>\n",
       "      <th>e</th>\n",
       "      <th>id_index</th>\n",
       "      <th>chrom</th>\n",
       "      <th>peak_start_ext</th>\n",
       "      <th>peak_end_ext</th>\n",
       "      <th>id_index_id</th>\n",
       "      <th>g1_enh</th>\n",
       "      <th>g1_onTSS</th>\n",
       "      <th>bm_enh</th>\n",
       "      <th>bm_onTSS</th>\n",
       "      <th>g1_other</th>\n",
       "      <th>bm_other</th>\n",
       "      <th>frac</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250</td>\n",
       "      <td>250</td>\n",
       "      <td>250</td>\n",
       "      <td>250</td>\n",
       "      <td>250</td>\n",
       "      <td>250</td>\n",
       "      <td>250</td>\n",
       "      <td>250</td>\n",
       "      <td>250</td>\n",
       "      <td>250</td>\n",
       "      <td>250</td>\n",
       "      <td>0.118765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>122</td>\n",
       "      <td>122</td>\n",
       "      <td>122</td>\n",
       "      <td>122</td>\n",
       "      <td>122</td>\n",
       "      <td>122</td>\n",
       "      <td>122</td>\n",
       "      <td>122</td>\n",
       "      <td>122</td>\n",
       "      <td>122</td>\n",
       "      <td>122</td>\n",
       "      <td>0.057957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>0.044656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>191</td>\n",
       "      <td>191</td>\n",
       "      <td>191</td>\n",
       "      <td>191</td>\n",
       "      <td>191</td>\n",
       "      <td>191</td>\n",
       "      <td>191</td>\n",
       "      <td>191</td>\n",
       "      <td>191</td>\n",
       "      <td>191</td>\n",
       "      <td>191</td>\n",
       "      <td>0.090736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>404</td>\n",
       "      <td>404</td>\n",
       "      <td>404</td>\n",
       "      <td>404</td>\n",
       "      <td>404</td>\n",
       "      <td>404</td>\n",
       "      <td>404</td>\n",
       "      <td>404</td>\n",
       "      <td>404</td>\n",
       "      <td>404</td>\n",
       "      <td>404</td>\n",
       "      <td>0.191924</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   p  e  id_index  chrom  peak_start_ext  peak_end_ext  id_index_id  g1_enh  \\\n",
       "0  0  0       250    250             250           250          250     250   \n",
       "1  0  1       122    122             122           122          122     122   \n",
       "2  0  2        94     94              94            94           94      94   \n",
       "3  0  3       191    191             191           191          191     191   \n",
       "4  1  0       404    404             404           404          404     404   \n",
       "\n",
       "   g1_onTSS  bm_enh  bm_onTSS  g1_other  bm_other      frac  \n",
       "0       250     250       250       250       250  0.118765  \n",
       "1       122     122       122       122       122  0.057957  \n",
       "2        94      94        94        94        94  0.044656  \n",
       "3       191     191       191       191       191  0.090736  \n",
       "4       404     404       404       404       404  0.191924  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#group >2\n",
    "\n",
    "def g5p(id_freq):\n",
    "    if id_freq['bm_onTSS']>2:\n",
    "        return 3\n",
    "    else:\n",
    "        return id_freq['bm_onTSS']\n",
    "        \n",
    "def g5e(id_freq):\n",
    "    if id_freq['bm_enh']>2:\n",
    "        return 3\n",
    "    else:\n",
    "        return id_freq['bm_enh']\n",
    "\n",
    "id_freq['p']=id_freq.apply(g5p, axis=1).astype(int)\n",
    "id_freq['e']=id_freq.apply(g5e, axis=1).astype(int)\n",
    "\n",
    "g=id_freq.groupby(['p', 'e'],as_index=False).count()\n",
    "g['frac']=(g['id_index']/2105)\n",
    "g.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "78c87159-d505-43a2-a797-7e375d5db4c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>p</th>\n",
       "      <th>e</th>\n",
       "      <th>id_index</th>\n",
       "      <th>chrom</th>\n",
       "      <th>peak_start_ext</th>\n",
       "      <th>peak_end_ext</th>\n",
       "      <th>id_index_id</th>\n",
       "      <th>g1_enh</th>\n",
       "      <th>g1_onTSS</th>\n",
       "      <th>bm_enh</th>\n",
       "      <th>bm_onTSS</th>\n",
       "      <th>g1_other</th>\n",
       "      <th>bm_other</th>\n",
       "      <th>frac</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>0.090258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>0.031519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>0.031519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>0.138968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>0.075931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>0.042980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>0.034384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>83</td>\n",
       "      <td>83</td>\n",
       "      <td>83</td>\n",
       "      <td>83</td>\n",
       "      <td>83</td>\n",
       "      <td>83</td>\n",
       "      <td>83</td>\n",
       "      <td>83</td>\n",
       "      <td>83</td>\n",
       "      <td>83</td>\n",
       "      <td>83</td>\n",
       "      <td>0.118911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>0.090258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>0.032951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>0.024355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>0.073066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>0.091691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>0.047278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>0.030086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>0.045845</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    p  e  id_index  chrom  peak_start_ext  peak_end_ext  id_index_id  g1_enh  \\\n",
       "0   0  0        63     63              63            63           63      63   \n",
       "1   0  1        22     22              22            22           22      22   \n",
       "2   0  2        22     22              22            22           22      22   \n",
       "3   0  3        97     97              97            97           97      97   \n",
       "4   1  0        53     53              53            53           53      53   \n",
       "5   1  1        30     30              30            30           30      30   \n",
       "6   1  2        24     24              24            24           24      24   \n",
       "7   1  3        83     83              83            83           83      83   \n",
       "8   2  0        63     63              63            63           63      63   \n",
       "9   2  1        23     23              23            23           23      23   \n",
       "10  2  2        17     17              17            17           17      17   \n",
       "11  2  3        51     51              51            51           51      51   \n",
       "12  3  0        64     64              64            64           64      64   \n",
       "13  3  1        33     33              33            33           33      33   \n",
       "14  3  2        21     21              21            21           21      21   \n",
       "15  3  3        32     32              32            32           32      32   \n",
       "\n",
       "    g1_onTSS  bm_enh  bm_onTSS  g1_other  bm_other      frac  \n",
       "0         63      63        63        63        63  0.090258  \n",
       "1         22      22        22        22        22  0.031519  \n",
       "2         22      22        22        22        22  0.031519  \n",
       "3         97      97        97        97        97  0.138968  \n",
       "4         53      53        53        53        53  0.075931  \n",
       "5         30      30        30        30        30  0.042980  \n",
       "6         24      24        24        24        24  0.034384  \n",
       "7         83      83        83        83        83  0.118911  \n",
       "8         63      63        63        63        63  0.090258  \n",
       "9         23      23        23        23        23  0.032951  \n",
       "10        17      17        17        17        17  0.024355  \n",
       "11        51      51        51        51        51  0.073066  \n",
       "12        64      64        64        64        64  0.091691  \n",
       "13        33      33        33        33        33  0.047278  \n",
       "14        21      21        21        21        21  0.030086  \n",
       "15        32      32        32        32        32  0.045845  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def c5p(id_freqc):\n",
    "    if id_freqc['bm_onTSS']>2:\n",
    "        return 3\n",
    "    else:\n",
    "        return id_freqc['bm_onTSS']\n",
    "        \n",
    "def c5e(id_freqc):\n",
    "    if id_freqc['bm_enh']>2:\n",
    "        return 3\n",
    "    else:\n",
    "        return id_freqc['bm_enh']\n",
    "\n",
    "id_freqc['p']=id_freqc.apply(c5p, axis=1).astype(int)\n",
    "id_freqc['e']=id_freqc.apply(c5e, axis=1).astype(int)\n",
    "\n",
    "c=id_freqc.groupby(['p', 'e'],as_index=False).count()\n",
    "c['frac']=(c['id_index']/698)\n",
    "c.head(30)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "b5acc3e2-a8f4-4c43-8611-df8afafe0467",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAfQAAADtCAYAAABJeIdtAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAB+t0lEQVR4nO3dd1gUx/8H8PfdcfQiTZAOdkQREBVRURNRNCpq7KIomqjYe++KLfbesJfYuxGjggWjNBHFTlM60uuV+f3hj/uKtCt7NOf1PPck7s3OfO5u2NmdnZ1hEUIIKIqiKIqq1djVHQBFURRFUbKjDTpFURRF1QG0QacoiqKoOoA26BRFURRVB9AGnaIoiqLqANqgUxRFUVQdQBt0iqIoiqoDaINOURRFUXUAbdApiqIoqg6gDboEoqOjwWKxcOTIEdG2I0eOgMViITo6usJ9i9OxWCw8ePCg1PuEEDRq1AgsFgtdunQp9X5WVhbWrFmDNm3aQFNTE0pKSrCwsMDYsWMREhJSZjksFgvKysowNDRE165d4ePjg+TkZCk/fdW4ePEihg0bhkaNGkFFRQUWFhYYMWIE3r9/Xyrt9evXMWrUKLRs2RJcLhcsFqvcfHk8HlasWAELCwsoKSmhWbNm2LFjR6l0y5cvL/H9ff891lVPnjzB8uXLkZGRwWi+tM5L5sqVK3BxcYGmpibU1NTQokUL7N+/v0SaoqIiLF26FJaWllBUVIS5uTkWLFiA/Pz8Uvl9+PABHh4eMDMzg4qKCho2bIiZM2ciLS2tqj4SVcUUqjuAn42GhgYOHTpU6gDm7++Pjx8/QkNDo9Q+Hz9+hKurK5KTkzFhwgSsWLEC6urqiI6Oxt9//w0HBwdkZGRAS0tLtI+vry+aNWsGHo+H5ORkPHr0COvXr8emTZtw9uxZ/Prrr/L+qFJZv349DA0NsWjRIlhZWSEuLg5r166Fvb09nj59ihYtWojSXrp0CU+fPoWdnR2UlJQQHBxcbr6TJk3C8ePHsWrVKjg6OuKff/7BtGnTkJ2djYULF5ZKf/v27RLfJ5tdd899nzx5ghUrVsDT0xP16tVjPH9a5yu3bt06LFq0CBMmTMCCBQvA5XLx5s0bFBUVlUg3bNgw3Lx5E0uXLoWjoyMCAwOxevVqvHr1ClevXhWlS0lJQfv27aGpqYlVq1bBzMwMoaGhWLZsGe7fv4/g4OA6Xad/WoQSW1RUFAFAfH19Rdt8fX0JABIVFVXhvsXpxo0bR1RUVEhmZmaJ90eOHEmcnJxIixYtiIuLi2g7n88nLVu2JJqamuTly5dl5n3z5k2Sm5tbopznz5+XShcTE0NMTU2JhoYGSUxMFO9DV7GkpKRS2758+UK4XC7x8vIqsV0gEIj+39vbm5RXnSMiIgiLxSJr164tsX38+PFERUWFpKWlibYtW7aMACApKSmyfIxaZePGjWLVYUnROi+eoKAgwmazyfr16ytMFxgYSACQv/76q8T2tWvXEgDkzp07om0HDhwgAMjdu3fLTBsSEsLcB6BqDHqKhm9dU2PGjEHjxo2hqqoKY2Nj9OnTBy9fvmS8rGHDhgEATp8+LdqWmZmJCxcuYOzYsaXSX758GS9fvsSCBQtgY2NTZp5ubm5QVVWttGwzMzP89ddfyM7Oxr59+6SKn8ViYfLkyTh+/DiaN28OVVVV2Nra4vr161Ll96P69euX2mZkZAQTExPExcWV2C7uFcbly5dBCMGYMWNKbB8zZgzy8/Nx+/Zt6QOuRm/evMGwYcNgYGAAJSUlmJmZYdSoUSgsLER0dDQUFBTg4+NTar+AgACwWCycO3cOy5cvx5w5cwAAlpaWpbrIhUIhNmzYgGbNmkFJSQn169fHqFGj8PnzZ7HjpHW+Yjt37oSSkhKmTJlSYbrHjx8DAHr16lVi+2+//QYAuHDhgmgbl8sFgBI9GABEPTB1+RbSz4w26ADi4+Ohq6uLdevW4fbt29i1axcUFBTQrl07vH37ltGyNDU18fvvv+Pw4cOibadPnwabzcaQIUNKpb9z5w4AwN3dnZHye/XqBQ6Hg4CAAKnzuHHjBnbu3ImVK1fiwoUL0NHRQf/+/fHp0ydRGkII+Hy+WK/KfPr0CTExMSW62yUREREBfX19GBoaltjeqlUr0fs/atmyJTgcDgwMDDBq1CjExsZKVba8vHjxAo6Ojnj69ClWrlyJW7duwcfHB4WFhSgqKoKFhQX69u2LvXv3QiAQlNh3586dMDIyQv/+/TFu3DhRQ3Lx4kUEBgYiMDAQ9vb2AICJEydi3rx56N69O65evYpVq1bh9u3b6NChA1JTU8WKldb5iut8QEAAmjdvjgsXLqBp06bgcDgwMTHB/PnzS3S5F/+/kpJSif2L/x0eHi7a5u7uDjMzM8yaNQuvXr1CTk4OAgICsG7dOvTp0wfNmzeX+rugarBq7iGokfh8PikqKiKNGzcmM2bMEG1nosv9+fPn5P79+wQAiYiIIIQQ4ujoSDw9PQkhpFT3Y8+ePQkAUlBQIFbsFXU/FjMwMCDNmzcXK78fASAGBgYkKytLtC0xMZGw2Wzi4+Mj2lb8GcV5VfTd8Xg80qVLF6KpqUliY2PLTVdRl3v37t1J06ZNy3xPUVGR/PHHH6J/Hzt2jKxZs4bcvHmT3Lt3j6xbt47o6OgQAwMD8vnz53LLr2rdunUj9erVI8nJyeWmKf4NLl26JNr25csXoqCgQFasWCHaVl6Xe2RkJAFAJk2aVGL7f//9RwCQhQsXVhgjrfPi1XklJSWioaFBtLW1yc6dO8m9e/fIokWLCIfDIcOHDxelu3z5MgFAjh8/XiK+Q4cOEQCkSZMmJbbHx8cTJyenEuUOGjRI7O+Vqn3ooDgAfD4fGzZswIkTJ/DhwwfweDzRe5GRkYyX5+LigoYNG+Lw4cPw9PTE8+fP8ddffzFeTnkIITLt37Vr1xIDmQwMDFC/fn3ExMSItjk4OOD58+di5WdkZFRunF5eXnj48CEuXLgAU1NTqWOuaAT89+95eHiUeK9r167o2rUrnJycsGHDBmzbtk3qGJiSl5cHf39/eHl5QV9fv9x0Xbp0ga2tLXbt2iW62t27dy9YLBb++OOPSsu5f/8+AMDT07PE9rZt26J58+b4999/sWbNGrFipnW+pO/rvFAoRHZ2Nk6fPo2hQ4eKysvNzcXWrVuxYsUKNGrUCG5ubmjUqBHmzZsHAwMDUQ/NwoULweFwStyCSk9PR79+/ZCXl4eTJ0/C1NQUERERWLVqFfr27YsbN25AQYEe/usa+osCmDlzJnbt2oV58+bBxcUF2traYLPZGDduXJmPg8iKxWJhzJgx2L59OwoKCtCkSRN06tSpzLRmZmYAgKioKDRr1kzmsnNzc5GWloaWLVtKnYeurm6pbUpKSiW+K3V1dbRu3Vqs/Mo6sBBCMG7cOJw4cQJHjx5Fv379ZIo3LCys1Pbc3FwUFRVBR0enwv3btm2LJk2a4OnTp1LHwKT09HQIBAKYmJhUmnbq1KkYN24c3r59CysrKxw4cAC///57qdsPZSl+vKlBgwal3jMyMirRmFWG1vmSvq/zurq6SExMRI8ePUqkcXNzw9atWxESEoJGjRpBUVERt27dgoeHB1xdXQEAampqWLt2LVatWgVjY2PRvuvXr0dYWBhiYmJEv1+nTp3QrFkzdOvWDSdPnsTo0aPF/vxU7UDvoQM4ceIERo0ahbVr16JHjx5o27Yt2rRpI/Y9Qml4enoiNTUVe/fuLTVY63vFf+SXL19mpNwbN25AIBCU+dwvk/z9/cHlcsV6/fgMf3Fj7uvri4MHD2LkyJEyxdKyZUukpKQgMTGxxPbiQY/lDbz6Maaa8piPjo4OOByOWAPThg8fDl1dXezatQvnzp1DYmIivL29xSqnuBFLSEgo9V58fDz09PQkipvW+bLrfPFYjh8V9yp8X+8aNWqEwMBAfP78GeHh4UhOTsagQYOQmpqKzp07i9KFhYXB2Ni41MmYo6MjgLLHjVC1H71Cx7erhx8Hmty4cQNfvnxBo0aN5FKmsbEx5syZgzdv3lR4ptyvXz+0bNkSPj4++O2338psfP755x906tSp0lG/sbGxmD17NrS0tPDnn3/K/BkqIm33IyEE48ePh6+vL/bt21fhgV9c/fr1w+LFi3H06FHMmzdPtP3IkSNQUVFBz549K9z/6dOneP/+PaZOnSpzLExQUVGBi4sLzp07hzVr1lTYsCorK+OPP/7Azp078eTJE7Ru3RrOzs4l0hTX/R97o7p16wbg2wlvcUMAAM+fP0dkZCQWLVokUdy0zv/P93V+4MCBuHPnDm7duoXhw4eLtt+8eRNsNrvEd1/M2NhYdEW+ePFiqKmpwcvLq0T+//77L758+VLiyj0wMBAAxOrdoWof2qDj22MfR44cQbNmzdCqVSsEBwdj48aNcq/069atqzQNh8PBpUuX4OrqCicnJ0ycOBFdu3aFmpoaYmJicP78eVy7dg3p6ekl9ouIiBCNqE1OTsbDhw/h6+sryu/7e6/R0dGwtLTE6NGjS8yCJwsNDQ20adNG4v2mTp2KQ4cOYezYsWjZsmWJbm4lJSXY2dmJ/h0TEyM6gH78+BEAcP78eQCAhYWFqPwWLVrAy8sLy5YtA4fDgaOjI+7cuYP9+/dj9erVJbrcbW1tMXLkSDRv3hzKysp49uwZNm7cCENDQ8ydO1fyL0JONm/ejI4dO6Jdu3aYP38+GjVqhKSkJFy9ehX79u0rcb930qRJ2LBhA4KDg3Hw4MFSeRV3RW/btg2jR48Gl8tF06ZN0bRpU/zxxx/YsWMH2Gw23NzcEB0djSVLlsDU1BQzZsyQOG5a50sbM2YM9u3bh0mTJiE1NRXW1ta4e/cudu3ahUmTJsHc3FyUdsOGDTA0NISZmRmSkpLw999/4/Llyzh+/HiJhtvb2xsnT55E9+7dMX/+fNE99NWrV8PAwAAjRoxg5DNTNUz1jcerOdLT04mXlxepX78+UVVVJR07diQPHz4kLi4uJUbfMjXKvSI/jvgtlpGRQVatWkXs7e2Juro64XK5xMzMjIwcOZI8fvy4VDnFL0VFRVK/fn3i4uJC1q5dW+ao6JcvXxIAZP78+RXGRsi3Eb/e3t6ltpubm5PRo0dXun9lzM3Nyx0ZbG5uXiLtj5/1+9ePsRQVFZFly5YRMzMzoqioSJo0aUK2b99eqvyhQ4eSRo0aETU1NcLlcom5uTmZMGECiY+Pl/mzMe3169dk0KBBRFdXlygqKhIzMzPi6elZ5ijmLl26EB0dHZKXl1dmXgsWLCBGRkaEzWYTAOT+/fuEkG+T96xfv540adKEcLlcoqenR0aOHEni4uIqjY/WefGlpaWRP//8kxgYGBAul0uaNGlCNm7cWGLyJEIIWbFiBWnYsCFRUlIi9erVIz179iQBAQFl5hkSEkL69+9PTExMiJKSErGysiLjxo2r8GkRqnZjESLj8E+q1tu9ezfmzp2Ljx8/wsDAoLrDoRiWnJwMc3NzTJkyBRs2bKjucGoEWuepuoh2uVO4f/8+pk6dSg9sdcznz5/x6dMnbNy4EWw2G9OmTavukGoMWuepuoheoVNUHbV8+XKsXLkSFhYW2Lx5M2Mzr1EUVTPRBp2iKIqi6oCa8WAtRVEURVEyoQ06RVEURdUBtEGnKIqiqDrgpxrlLhQKER8fDw0NjQoX66AoSRBCkJ2dDSMjI7lND0vrLiUvtP7WLLL8Hj9Vgx4fHy/Til0UVZG4uDi5zS5I6y4lb7T+1izS/B4/VYNePB1mXFwcNDU1qzkaqq7IysqCqalpielWmUbrLiUvtP7WLLL8Hj9Vg17c1aOpqUkrFcU4eXYl0rpLyRutvzWLNL8HHRRHURRFUXUAbdApiqIoqg6gDTpFURRF1QE/1T10iqIoSj4EAgF4PF6Z7xUVFcHc3BxFRUUoKCio4shqFg6HAwUFBbmMWaANOkVRFCWTnJwcfP78GeUtDSIUCrF3714kJSUhJSWliqOreVRVVdGgQQMoKioymi9t0CmKoiipCQQCfP78GaqqqtDX1y/zylMgECA/Px8WFhbgcDjVEGXNQAhBUVERUlJSEBUVhcaNGzM6mQ9t0CmKoiip8Xg8EEKgr68PFRWVMtMIBAIAgLKy8k/doAOAiooKuFwuYmJiUFRUBGVlZcbypoPiKIqiKJnRKV3FJ68pdmmDTlEURVF1AO1yp6ifVGFhIa5euYwnd/7Bu9evwOYXAYSAsFjgqmmgVZs2+KWPOzp16kSvviiqFqANOkX9ZNLT07F+2RIE+99DP30VeOmro3ErXXDY/2u0C/gChH/6D9cX3cfKPCEGjfHCuInecrn/+fHjR5w+eBAhjx8h7+tXsIQCACwIuFyYNmwIl9/6YNCwYeXen6V+XiwWC5cuXYK7u3t1h1Ij0AadAYQQREdHIzgoCCkJCWBz2LBq0hQODg7Q0dGp7vAoSuT6lcvYvGQBFjWsh1UdLMq98lZW4KCtQT20NaiHIoEQR64cQ++TJ7DtyHE0bdqUkViCg4OxctpUqCYnYoCQh8EqylBVKL4LSEBIIRLehCMgPAS9fdaiTffuWLZxE9TU1Bgpn6r5kpOTsWTJEty6dQtJSUnQ1taGra0tli9fDicnJyQkJEBbW7u6w6wxaIMug7S0NOzfvhV3r1xCUzUF2KmyYaLIgYAQhF8k8M0qQqaiKkZM8MaQ4SN++tGdVPUhhGDpnJnIfHwXV9qbQ0VB/LqoyGHjj8YG6JmdD+/f+2Kqzya4/dZH6lh4PB6Wz56NtzeuYrkSB/qqXADcUulYLBaMFLkYqsjFUAD+d2/BzeEeVu3ZC5euXaUuvyICgQDPnz9HSkoKCgsLoa2tjRYtWsDQ0FAu5VEVGzhwIHg8Ho4ePQorKyskJSXh33//xdevXwGA/i4/oIPipHTu9CkM7uKMViF3cMvJDNttjTGmcQO4mdfHbxYGmNbUEMcczXDSuh5SjmxDL+f2iIyMlGtMwcHBmOwxEv07d0Lvdu0wzLU7tvj4ICMjQ67lUjXf0jkzoR4SgM12ZhI15t8z01DBOSdLHFw8B3du3ZIqj8LCQgzp2QMNbl7BVnUl6HPFv6ZwUVXGPq4QW73G4MyxY1KVX56kpCSsmD8fzk2aYteA33FntBceef2Jc8NGwqNdewzo1g33790rd+IUinkZGRl49OgR1q9fj65du8Lc3Bxt27bFggUL0Lt3bwDfTvouX74MAFi+fDlYLFap15EjRwB8O6ndsGEDrKysoKKiAltbW5w/f15UXnp6OkaMGCF6/K5x48bw9fWt6o8tE3qFLiFCCBZOnwp+UACudbCEIqficyJ1rgK8mxrCPacAEwe7Y/qGrXB1c2M0nmOHDuHEzh1omJeDwWwhzBW54LJYyMn7iseH9mDY4UMwatUKc9f6MNZdStUeVy5cQNbju1hmZyZzXsoKHBxpa4EBc2fAxtYWRkZGYu9LCIFnf3e4f4lGNzXpnr3V4HCwRYONWSuWop6ODnr+9ptU+Xwf06IZMxF48RK6ZOVgPlsBbBYLYHEABQ4gAJBTiNTQCBweMQrL9LRx7No1WFhYyFRuZdLS0hAQEIC0lBSoa2qiVatWsLa2lmuZNY26ujrU1dVx+fJltG/fHkpKShWmnz17NiZMmCD698mTJ7F06VK0adMGALB48WJcvHgRe/bsQePGjREQEICRI0dCX18fLi4uWLJkCV6/fo1bt25BT08PHz58QH5+vlw/I9Nogy6hdcuWQDP8MebYmki0n7G6Mv52ssTweTOgpa2Ndu3byxxLUVER/hgyBCYvQ7FbVREqqiW7LTU5HLipq8INwIdXofB264m5O3fBtVcvmcuuzIcPH5CcnAxlZWU0a9YMqqqqci+TKu3r16/YtnwxrjqZM5anigIHm1rUx9Qxo3Dutp/YI+B99+5Fww9v0U1VtukuFVgsrFdThNeM6Wjn7Cz1PVShUIixgwZB7VEgZvAJwCnd7V9Mj83BoCIBkuOSMLRLVxy8fg02NjbSfoRyBQcHY+2SpfgUHgHt5HQo8HgQstjI0dMCu0F9TJo1E8NG/By37xQUFHDkyBGMHz8ee/fuhb29PVxcXDB06FC0atWqVPriEwAAePr0KRYvXoyjR4/CxsYGubm52Lx5M+7duwcnJycAgJWVFR49eoR9+/bBxcUFsbGxsLOzE50AyPukTR5ol7sEgoODEX79IuY0byDV/soKHBxyNMPCieNlPvMjhMBr0O/o8OoFJqgrQ6WSiQoaKSthjzoXWydPQsCDBzKVXR4+n49De/fCxaYl5nT9BYcGDsbWPu7obm2DyZ6eiI6Olku5VPnWLVmEJY20oSxlN3t5WuhooGleKu76+YmVPiUlBSf/2oTxKuU3mpJQZrMxmy3A7PHjpM5jjrc3NB8Fogdf/G70+hwOJmXmYlzffoiPj5e67LL8tX49xvf8DYq3/NHuSzqa8AArcNGIcNA6JQfNwj/i0KTp6PNrd+Tl5TFadk01cOBAxMfH4+rVq+jRowcePHgAe3t7UTd6WWJjY+Hu7o7Zs2dj8ODBAIDXr1+joKAA3bt3FzX86urqOHbsGD5+/AgAmDhxIs6cOYPWrVtj7ty5ePLkSVV8REbRBl0CiydPxF+txO9iLIu2EhcTjVWxec0qmfLZvXkzmrx+iV4SXO2osNnYoqaIxeO8kJ2dLVP5P8rPz4d7t24IWbwMk+NTMCavCP2KBPi9gId52fmwvHQdwzq7yO1koiyfP3/Gnl27sHXTJjx79uynu/+Zn5+P0IcP0NGwnlzyn9hQDwf+2iBW2v1bt2AMiw8Og8+z26koITX8BRITEyXeNzIyEq+vXsevEjTmxeqxORielon5kyZJvG95dm/fjnPrN8MxNQda5RyWFcFC01w+uI+CMLBXb9F0qnWdsrIyunfvjqVLl+LJkyfw9PTEsmXLykybm5uLvn37wsnJCStXrhRtFwqFAIAbN24gLCxM9Hr9+rXoPrqbmxtiYmIwffp0xMfH45dffsHs2bPl/wEZRBt0MQUFBaEZuwj1VSu+jyOOvqa6uHftCvh8vlT7E0Lw98ED8JCi61KNw8ZQFh/HDuyXquzyjO7fH20j3qAHYUOpjIN2YwUuZuQUYL7HKLx7947Rsn+Ul5eHwX36wr2tEy5PnoM7c5ZiRq9+cGpli7dv38q17Jrk8oULGFBfVW6TwhiqKoHzNQnJyckVphMKhfC7cAGdVZmbs7rYYMLDga1bJd5v66rV6JEjfS+ZhQIXMWEvkJ6eLnUexVJSUrDHZwNs0/PAQuW/VQM+UPAsDL4HD8pcdm1kbW2N3NzcUtsJIRg5ciSEQiGOHz9eot5bW1tDSUkJsbGxaNSoUYmXqampKJ2+vj48PT1x4sQJbN26Ffv3M3uclLda0aBHR0fDy8sLlpaWUFFRQcOGDbFs2TIUFRVVWQwn9+3GKBMNRvJis1jopq2Ihw8fSrX/v3fvoi2/EApSHqh7qijjwuHDjF2xhoWFQRDxGq1ZFXfrKrPY8MjOx6o5cxgptyyEELj36InC2/5ok5AJSyjADApomZaLxhGf8LtrTyQkJMit/Jrkyd1/0NWAmTpbHmctRTx9+rTCNO/fv0dTCL8NNmNYR1VlBP57V6J9cnJy8OrJE1gpyNb93zEzB4d27ZIpDwDYtWUrzJIzxWrMi1nl83Fg+w6Zy67J0tLS0K1bN5w4cQLh4eGIiorCuXPnsGHDBvTr169U+uXLl+Pu3bvYt28fcnJykJiYiMTEROTn50NDQwOzZ8/GjBkzcPToUXz8+BGhoaHYtWsXjh49CgBYunQprly5gg8fPuDVq1e4fv06mjdvXtUfWybV2qDHx8eLdZX65s0bCIVC7Nu3D69evcKWLVuwd+9eLFy4sAqi/OZtRARa6DB3cGynpYRnAQ+k2vfwX5swRFH6e6KKbBZaFBUgKChI6jy+t3XlSvwi5tWOMUcBsS/CGbmyKcujR4+Q9+otGpTRlaoGNhrGJmP9d11xddnHt2/QUFO+gxHttZQR/NC/wjRB//2HFkUFcimfw2JBkJ0l6lIVx5VLl+CQlSNz2W1YHFw/c1amPAghuHTmDIzFDx8AwAULnOSvCAkJkan8mkxdXR3t2rXDli1b0LlzZ9jY2GDJkiUYP348du7cWSq9v78/cnJy0KFDBzRo0ED0Onv222+0atUqLF26FD4+PmjevDl69OiBa9euwdLSEgCgqKiIBQsWoFWrVujcuTM4HA7OnDlTpZ9ZVtU6yv3AgQPYs2cPRowYAU9PT7Rs2bLMdD179kTPnj1F/7ayssLbt2+xZ88ebNq0qdz8CwsLUVhYKPp3VlaW1LGyigoYvcJooaOOEy9Cpdo3PSUFhhI8v1uWhrxCREdHw9HRUaZ8ACD6dSQGcMSPp0VOHgIDA9FLDqPt9/y1BabpuSjvXNUAbPjfEW8gV3Viou6yeUVyn4O9oZYqot5VfBvjXVgoHBXkd+2gByA1NRX169cXK33cx4+ozxcAMv4NcVgssGTsJczIyIBSIQ9sCa7Oi2mkpiP4+XPY29vLFIM8CIXCEj2A0tzvV1JSgo+PD3x8fMpN830ZDyoZn8NisTB16lRMnTq1zPcXL16MxYsXSxxnTVKtV+jz5s3D9u3b8fbtW9jb28Pe3h7btm1DSkpKpftmZmZWOq2qj48PtLS0RK/v75VIig1mB1SpKHBQWFBYecKyMDAYRpUQ5GRlypwPAInjUSrilXkPjAkpyclQq+DgyAIL4Nf8wURM1N2qWE5Fkc0Gj8erME1RYSEU5XhiwQUkuv2Wm5VV5jgPaQhl/FvMy8sDR8pDiwJYyJRTT5esEhMTERoaKnqFh4dXd0g/hWpt0JWVlTF48GBcv34dX758wahRo3D06FEYGxvD3d0dly5dKrNL/uPHj9ixY0eJSQTKsmDBAmRmZopecXFxUscqZDH7VWUU8qChqSndzhJcDZcni8VCPR1dmfMBAKGCgkT347NVlOU2x32T5s2QjvL7L4Ug4CgzPziLaUzUXQl7caWSzxdApZI5BtQ0NJErQZe4pPIIkWieg3q6ushjaPwIW0G2v0VNTU0USXluUQRAT8xeiapmaGgIOzs70aus58Yp5tWYQXH169fH9OnTERISgitXriAwMBADBgxAREREiXTx8fHo2bMnBg0ahHHjKn4GVUlJCZqamiVe0lJQU0eRgLmD0ovULNi27yDVvpbNmuJNvpRX98Xlc5UZmxijQ/df8UpQ8VVaMUIIXqkpo1OnToyU/aOpc+cgpr5Wue/HclkYMnqUXMpmEhN1l6OqBh6DdbYsr9Nz0My2dYVpbNq3xzs5hpHBUZDoBLG5rS3ilGV/WiWPCMHVkG1cjYaGBjhamuBJ0QOYbqiLrr/8IlP58sJms8HhcEq8KPmrMQ16dnY2fH190a1bN/Tp0wc2NjY4evRoiekO4+Pj0bVrVzg5OVX54wT2Ts54mpTBWH4BWXw4dXaRat9JCxbiJJH+p8sUCJCuo4vGjRtLncf3Js+di7ua4q2A9VLAQ8eePaGoKNtsYeVp2rQpnPv3Q6SGEoQ/HCQT2ARZ1g3hPX2aXMquaaxtW+N1uuyDvyoSks2DY8fOFaZp06YNwhXk83vnC4VQlnCmuB5ubojQUINQxqv0RxwWPKdOkSkPABg/dTJilSW70s+DENqWZjA3Z24GQKr2q9YGXSAQ4NatWxg+fDgMDAzg4+ODbt264dOnT/j3338xatQo0YH/y5cv6NKlC+zt7eHr6wt2JTOjMc1zojcOf2FmMpYCvgDhBYCdnZ1U+9vY2CBRsx6ypbx/dz6fj7GzmJswwcTEBJ2GDsFVhYr7DhMEfNw01MeC1asZK7ssW/fsRv8l8/DMyhAR+hqI1FVHoIk29Ib0xZ1HD3+aaWi7/dYPN5PlM1ahWEB6QaUDK01MTJCsrIp8OXS738wrQu+hwyTah8PhoOeg3/FCKN08EMC3nqZgDVX8PnSo1HkUGzl6NBL0tVAkwVX6G201zF1e9uQq1M+rWhv0tWvXYtiwYVBXV8fdu3fx7t07LF68GGZmJReRiI+PR5cuXWBqaopNmzYhJSVF9IxhVTE3NwdpYI6XadKPlC+250MKPCZOlmkE8tRly+GTx5f4WfKYwiI8UFVH3/79pS67LMs3bIDB8CHYraKAT/yS3e+5QiFucYDjJgb4+9+7cl8jnsViYfqc2Qh5/xb7H/hh292beBz5CodOnRTN9fwz+LV7dzzIKAJfTvevX33Nhol1S7G+0yETJuBGnmy3iX5ECME1lgJGjh0r8b4TZszAPxqqEEh5lf4cBJ179Wakp0lFRQX7Tp3AcwPNSht1AoI3mkpwGTkU3V1dZS6bqluqtUH38PBAYmIi9u/fjw4dyr+ffOfOHXz48AH37t2DiYlJiWcMq9KmfQcx93WKTPfS36bn4BHU4THWS6ZY3Pr0QavRY7A+t0jsRj2uiIf5fDaOXr8BBRkH8/yIxWJhzZYt2HrXD2/7uGF9PVX8pa6MTZoqOGRlgq7bNuN+aChMTCRb1EYWbDYb1tbWaN269U/VkBdjs9noO9wDp6NT5ZL/Xx+/wnv+IrHSjvAcg0tcFWQxOF3plfwiuAwcCDU18W73fM/AwACTV62Cr7JkAzoB4KOAj0ArM6zYtFHicsvj3LEjdv99Gs9MdRClyILgh4adgCARAjw30ITLpHHYsG0rY2XXFOHh4di5cydWrlyJnTt30pHxUmCRn2iC66ysLGhpaSEzM1PqAXLXLl3EqVWLcdjRHNxKlk79UWx2PrxeJOLELT8YGxtLVf6Pdm3ahH9278JEBYKW5UytmS8U4npeIa4oq+PI9RtVtoqQQCAAm82W+7PQ1Y2JeiWvMng8Hnp1aAffFjowZGDa4mI349LwwLglNu89IPY+D/39sdfLE+vUFGWuE4k8PuZz1XDreRC4XOlnfNu1eTOubdqM8QV8cMWI6QUR4J65CS7IqacpJycHvgcO4Oje/eBk50JRIISAzUIOlwOXHq6YuXCBaCIUpshafwsKChAVFQVLS0sol/MEiUAgQGhoKOzs7EoMkBMKhTh69Cg2b96MpKSkEo8s6+vrw8DAALNmzcKoUaOq/DarPFX0ncnye9AGXQoX/z6LQ6uXYbutEcw1VMTa5278V2yIycGhi1cZ/4N8+/YtdvmsxevHj9FDWARzFqDEYiFLIMATBSW8V1HDsIkTMXy0J1RUxIuXEl9NbtCBb1c+i0cOwlknK4lPQssSl5OPcRGpuP74P4nr0+oF85F94W9MkWEJ1a98PqbmC7Hv5i00bdpU6nyKXbt0CevmL4BVVg66FRRBl11yRLaAEAQRAR5pqaNJ+3bY7usr978jQgiSk5ORkZEBVVVVGBgYyG0gaXU16AUFBejTpw+ePHlS4epxqqqq6NChA65du1Zu/rUNbdAZwOSB9/3795g2xgP27EKMs9CGiXrpP3BCCJ4lZ2JPbCZ0WjnCZ/tOqboHxZWbm4trly/j86ePKMjNhbZ+fbTt3JmR2eCo8tX0Bh34dhJ6bt0KHHI0h6IMjXpcTj7Ghibg0JUbsLKyknh/QghWzJ2DuIvnMV9NsdJlf38UmV+AVUIOdpy/CFtbW4nLryiuB/fvY8fq1Uj++AlaLBYUCJAHIFdJEQNGecDL21vqtddrsupo0IVCoWg5VHGm/+ZyuXBxccE///xTJ67U5dWgS3wj9fbt21BXV0fHjh0BALt27cKBAwdgbW2NXbt21ckKX5bGjRvjxsNAPHjwAIs2b8TXiFgYK3FQX5EDASGIzuMhExzYOLbDig1z0bBhQ7nHpKamhqEjRsi9HKr2GTB4CDgcDgYsX4ytrQzRSEvyE8vbn79ic1wODl6+LlVjDnwba7F84yZcd+4Ir7mz8QcpRGdV5UqnVc4UCHA4n48Yi4b4+8RJGBoaSlV+RXF17dYNXbt1g0AgQEZGBgoLC6GtrU17teTg6NGjePLkidgrTvJ4PDx58gTHjh2Dp6cnY3EEBARg48aNCA4ORkJCAi5dugR3d3fR+z4+Prh48SLevHkDFRUVdOjQAevXry/VM7R7925s3LgRCQkJaNGiBbZu3Sq3uTYqIvGpzpw5c0TzSr98+RKzZs1Cr1698OnTJ8ycOZPxAGsyFouFrl274uS1m7gZHI6VF25iyPbD8Nh9DAfuPcbtoDBs2rOvShpziqpMv4G/Y++125j7RYB1r+KRViDedKlv03Mw7nkM7hnZ4Prj/xipz7+5u+PqsyB8dB8Mj3whduUW4nF2LjL4AhBCvp0UFxbhalYu5ufxMVdVB503bMI5v7uMN+Y/4nA40NXVhZGREW3M5WTz5s0VdrOXJS8vD5s3b2Y0jtzcXNja2pa52AvwbcEXb29vPH36FH5+fuDz+XB1dS0xdfXZs2cxffp0LFq0CKGhoejUqRPc3NwQGxvLaKzikLjLXV1dHREREbCwsMDy5csRERGB8+fPIyQkBL169arSR8kkVRVdo9TPpzZ0uX+PEIJrV67Ad9tmaOZmoKOWAuy11dBQSxVcNgt5fCFefc1GcGYh/NMLYdisBbznL2K0i/t7fD4fjx49wrMHDxD65AmyMjPB5rBham4Ox26/oFPXrmjUqJFcyqaqvsv91atX+PXXX8Vas+NH+vr6uHv3rlymkmWxWKWu0H+UkpKC+vXrw9/fH507f5tQqV27drC3t8eePXtE6Zo3bw53d/dyF5apMV3uioqKojOru3fvYtSob9No6ujoyLSaGUVRVYPFYqGvuzv6urvj8+fPCHzyBOcePkD0hw/g8YqgqqqK5rbd0KaTC8a3by/3k18FBQV06dIFXbp0kWs5VM0QEBAgVWMOfGtQHz16VG1zw2dmflvQqvgJh6KiIgQHB2P+/Pkl0rm6uuLJkydVHp/EDbqzszNmzpwJZ2dnPHv2TLTW7Lt376r0GWOKomRnYmKCQYMHY9DgwdUdCvWT+Pr1q0z7p6bKZ16FyhBCMHPmTHTs2FG0DkZqaioEAgEMDAxKpDUwMKiW3mqJ76Hv2rULXC4X58+fx549e0TPU9+6davEmuUURVEU9SNZn9/X09NjKBLJTJ48GeHh4Th9+nSp936cV4EQUi3zb0h0hc7n83H//n3s37+/1CxtW7ZsYTQwiqIoqu7p3Lkz9PX1pb6HXvyEVVWaMmUKrl69ioCAgBI90Xp6euBwOKWuxpOTk0tdtVcFia7QFRQUMHHiRBQViTc6lqIoiqK+16pVK6kbO0NDwyq9f04IweTJk3Hx4kXcu3ev1KRgioqKcHBwgJ+fX4ntfn5+FU5nLi8Sd7m3a9cOoaGh8oiFoiiK+gnMnDlT4lUPVVVVMWvWLEbjyMnJQVhYGMLCwgAAUVFRCAsLEz1y5u3tjRMnTuDUqVPQ0NAQLQqWn58vymPmzJk4ePAgDh8+jMjISMyYMQOxsbGYMGECo7GKQ+JBcZMmTcKsWbPw+fNnODg4lJr5rLpGH1IURVG1w+jRo3Hq1Cn4+/uDx+NVmp7L5aJDhw7w8PBgNI6goCB07dpV9O/iuVRGjx6NI0eOiB5F+/EJDF9fX9EEN0OGDEFaWhpWrlyJhIQE2NjY4ObNm9WyVr3EDfqQIUMAAFOnThVtY7FYokEAAgZXU6IoiqLqHjabjWvXrok9l7uzszOuXr3K+LSvXbp0qXC1PXGnaZk0aRImTZrEVFhSk7hBj4qKkkccFEVR1E9EWVkZ//zzD44dO4bNmzcjMTGx1GprhoaGmDVrFjw8POrEHO7yJnGDXh3dCBRFUVTdw2az4enpCU9PT4SHh+PRo0dITU2Fnp4eOnbsSG/hSkjiBh0Ajh8/jr179yIqKgqBgYEwNzfH1q1bYWlpiX79+jEdI0VRFFXHtWrVijbgMpK4D2PPnj2YOXMmevXqhYyMDNE983r16mHr1q1Mx0dRFEVRlBgkbtB37NiBAwcOYNGiRaKF6gGgTZs2ePnyJaPBURRFUT+HoqIixMfH4+3bt4iPj6fznUhBqkFxdnZ2pbYrKSmVWFLuZ0QIQXZ2NrhcLl12kaIoSgwvXrzA8uXLERQUBIFAAIFAAA6HAw6HA0dHRyxfvpx2xYtJ4gbd0tISYWFhpQbH3bp1C9bW1owFVlsQQvDff/9h75ZNSIiJgo6qMvhCIdLzC+HU5Rf8OWValS5ak56ejpcvX6KgoAD6+vpo3bp1tcwpTFHSSE9PR1JSEhQVFWFiYgJFRcXqDomSk3fv3mHw4MGIj48vdxrYz58/49GjRzAyMsK5c+fQuHHjKo6ydpG4QZ8zZw68vb1RUFAAQgiePXuG06dPw8fHBwcPHpRHjDVWeno6xgwdhCZqbCzuYAPLXv9bL5oQgofvYjDLYxAaOzpj1fqNcm1YX7x4gW2rV+Drx7dwqqcMJRYQX0QwJ4eH3kOGY/zkKVBXV5db+VTtFRERgd2bNyH6/VtwWACPAC7de2DcRG/o6+vLvXxCCG7fuomDmzeBk5ECU1VFFAoI3mQXok2Xbpg4a06VPl1DCEF8fDwKCgpgaGhYavIseePz+bh2+TKO7tyFnMxMsBUU0L1vX4yb7A1tbe0qjUVeAgMDMWjQIHz58qXStCkpKUhJSUHXrl1x7tw5ODk5VUGEtROLiPvk/HcOHDiA1atXIy4uDgBgbGyM5cuXw8vLi/EAmSTLwvFl5TXAzRVrXe3gYGFUYdpdD0LxUUkPW/fsk0ujfuLwIVzevgmrWxigkVbJgw9fKMTlmFQcTBXg5PVbVbZgQEFBAeLj46GhoVEljUJ5CCEghMj1GVYm61VVllFYWIiJY0dDKT0JE5xbwMbkW90QCoW48+oT9jx5hd7DPDBxyjRGyisLj8fDHyOGwij+A7wb6aO+qpLoPUIIApMysPZ9Gqau2YheffvKLQ7g2/exd+tWXDp6BGYCPpRZQJyAwKBFC8xZsxYtWrSQa/kAEPDgAeZ4jYNtTi5cioTQYLMhIARBRICHmmroPnwYFq9dy+hxRNa6VVBQgKioKFhaWkJZWbnMNAKBAKGhobCzs8PHjx/RrVs3sRrzHxkbG+P+/fu1/kq9ou9Mlt9Dqga9WGpqKoRCIerXry9tFlWKyYPimKGDMa6JNto3FK87fcWNJ7DuNxJDR4yQqdwf3b5xHceXzsVhRwtw2OX/kb/+mo1Zn3JxLeBxuX90TMjIyMDiqVPx9mkgLNgsZBAh8urpYNbq1ejW3VVu5f4oKCgIPvPmIfHjJ3AIAVtLE+NmzMQIz9GMn1TVxgZdKBRi5O/9MchcE31bNykzDSEEcy76o0n3fpg4ZWqZaWQ1wWMEOqd9wGCL8pfELBQIMPJpNGbvPADnTp3kEkdeXh5+/+UX9EiOR191ZXC/qyNRhUVYUyjEtK3b4SbHk4pHAQGYP2wEJucXQZVV+gSUEIKrXDb0hwzCuu3bGCu3qht0BwcHvHjxQup4bW1tRXOv11byatAlvmyJiorC+/fvAXxbOq64MX///j2io6MlzU5sPj4+cHR0hIaGBurXrw93d3e8fftWbuVVJD4+HvnJn8VuzAFgzq9tcGTfbkbjIIRg09LF2OtgVmFjDgDWOhoYVA84ffwYozF8LzMzEwNcOqPb0wD4qnKwTJmNLSoK2JiXjp1//oELZ87IrezvXb98GXP6uaN3yEvMyy7A7JxCTPqcBL95CzF93LgqiaGmu3L5Mloo8cttzIFvUzpvHOCC66eOIS0tjfEYXr58CfL+ZYWNOQAocTg42MYMq+cyuzDH96aM8oDn10QM1FAp0ZgDgKWSInapK2LzjGmiRTuYJhQKMWfcuHIbc+Db79GPTxBx4aJMDWJ1evHihVRX5t+Lj49HeHg4I/EEBASgT58+MDIyAovFwuXLl0u8z+fzsXjxYlhaWkJFRQVWVlZYuXIlhEJhiXS7d+8WNc4ODg54+PAhI/FJSuIG3dPTE0+ePCm1/b///hNNVi8P/v7+8Pb2xtOnT+Hn5wc+nw9XV9dqGVm/f9cOeLVtJtE+qkqKaFpPBSEhIYzFERgYCAdVFlQUOJUnBjDUXB9nD+5nrPwfbVq+DF55mWirWvKMU5PDwV8aSti+ZLHcH0UpLCzEqhkzMTmfDz32/74XZRYbAwUEcTf/QWBgoFxjqA2O7NmJPzvZVpqOxWJhvFNzHN6/l/EYdm/wwSSLemKl1VLiwgqFcmnIEhMTkRb+Ah1UlMpNo8RmYxJbiN0b1jNePgD8c+sWrLNyy23Mv9crtwBbV6yUSxzytnLlSqSmpsqUR0pKCpYvX85IPLm5ubC1tcXOnTvLfH/9+vXYu3cvdu7cicjISGzYsAEbN27Ejh07RGnOnj2L6dOnY9GiRQgNDUWnTp3g5uYmt5O/ikjcoIeGhsLZ2bnU9vbt28u1G+T27dvw9PREixYtYGtrC19fX8TGxiI4OFhuZZbn+eNH6NrMQuL9+rUwg9/N64zFcen4UQwxEn+gmyqXgwb49qwn0wgheHjzJjqrlt3lxmWx0IPwcfXSJcbL/t6VixfhmJNX6iqrmFt+IXauWSvXGGq6jIwMKPHyoa0m3qOVvVo2wr1bNxiPI+rVS7TQ0RA7/bAGarh08jjjcZw5cgTuwspPNNuoKuPZ3buMlw8Ax3ftRsfCylcdAwATjgLe1cIuZx6Px9jx+vnz54xcHLi5uWH16tUYMGBAme8HBgaiX79+6N27NywsLPD777/D1dUVQUFBojSbN2+Gl5cXxo0bh+bNm2Pr1q0wNTUVrdRWlSRu0FksFrKzs0ttz8zMrNKV1jIzMwEAOjo65aYpLCxEVlZWiRcTWEQo1X1YbTUVZKZ/ZSQGAMj4mgZ9Zcke69FX4iI9PZ2xGIoVFhZCs5LvpQmE+PjqFeNlf+9NeDhMKzgwGnAUkPg5Tq4xMEFedRf49nSGgab4I7c5bDYU5PCAhgIRVp7oO/VVlfA1JZnxOBJiomHMqbyXi8ViQUkon2NcWmoKtMW4Oi+mKBCAz+fLJRYmCIVC0TPlxa+MjAzGYhYIBHK5DfSjjh074t9//8W7d+8AfLtl8OjRI/Tq1QvAt8lwgoOD4epacnyQq6trmT3Z8ibxY2udOnWCj48PTp8+LZopTiAQwMfHBx07dmQ8wLIQQjBz5kx07NgRNjY25abz8fHBihUrmA9AyhHTuYVFUFMv/wREUqpqasgtlKz7KkcgkMtjOIqKisipZHxlEiHQNWrAeNnfMzQxwccKxhPkCIVQ0xD/qrC6yK3uAlBTU0N2gWRXNwKph86Wj0jQgAFADo8PNW3mfztNbR1kiHkxwpMwZnGpqqohnxCoiXmhwGexoaAg1VIcVSIxMbFUT2Bubm6pe8/SEggEyM7ORoMG8j2ezJs3D5mZmWjWrBk4HA4EAgHWrFmDYcOGAfg2MFwgEJR6esjAwACJiYlyja0sEtfODRs24N69e2jatCnGjBmDMWPGoGnTpggICMDGjRvlEWMpkydPRnh4OE6fPl1hugULFiAzM1P0Kn7MTlZmlg0R8TlJ4v0CPiXArm17RmIAgM5uvXEzsXRvSXkEQoI3OTyYmpoyFkMxNpsNK1s7vCsoLDfNNbYiBg4ZynjZ3xs0fDgCtdTLXcf4AZcNz6nyGbHNJHnVXeDbspRfcgpRyBPvaun5py+wti09O6Ss1PQNkJhXfn350Y2kXHTp/RvjcfQfORLX2dxK030qLIKpnCbP6jNsGJ6JeTTOEAqgbVp1k1VJw9DQEHZ2dqJXq1atoKamxtjjoxwOBxpVcGJ+9uxZnDhxAqdOnUJISAiOHj2KTZs24ejRoyXS/dgzSQiplgm9JP52ra2tER4ejsGDByM5ORnZ2dkYNWoU3rx5U+HVMlOmTJmCq1ev4v79+5XOwKakpARNTc0SLyZMnDEL+55I1nUsEArx74cE9HRzYyQGAOjXfwBupBZAKOaTh3c+p8G1/8ASc/AzaeGGDVjJYyGtjG61PbmF6NB/gNwnxtDW1kZPDw+cU+SU+l5eEAFiG1qib//+co2BCfKqu8C3g8/AER64EPJGrPT7Al9j4vSZjJVfbPysuTgcLd4tKL5QCP9MHrq79mA8Dmtra3zVM0BsYfm9FoQQ7C4SYsqSpYyXDwDDRnngqYaqWH/L/yoqwHvhArnEwRQ2my2avrX4Va9ePcZ6FTgcDnR1dRnJqyJz5szB/PnzMXToULRs2RIeHh6YMWMGfHx8AHx70ovD4ZS6Gk9OTq6yOT++J9XpkpGREdauXYsbN27g/PnzWLp0aYX3splACMHkyZNx8eJF3Lt3D5aWlnItryItW7ZEbL4QX9LFv695LigSPfr2Z3SCEwUFBfT3GI3NbyvvLcgo5GFLTBbGTZbf1amVlRV2XL6C2Vx1rM7j4XJGNo5k52N0Hh9awz2wZP0GuZX9vYWrV8F5/hys19XAGWUuLikpYKOGMr70csWle//W6K7KquLhOQZHw6LxNqHiWzZngyKhatYIDRs2ZDyGX7t3x38CZbxIq7yXaWlEPEZPniq3CYJ2nTmDeQIOPpZxK4JHCNbnFqH1cA/Y29vLpXwVFRWMnT0LJxQ55fYuAd9OSjOsm6F7D+ZPbOSNy+XCwcGBkbwcHR2rZFrgvLy8UnWOw+GIbh0oKirCwcEBfn5+JdL4+fmhQ4cOco/vR1Id2TIyMvDs2TMkJyeXuicyatQoRgL7kbe3N06dOoUrV65AQ0NDdEakpaVVLQuhbNl3EGOHD8LJ0T2hp1HxPelH72Nx9l0yzm+Zy3gc3rPmYOb7d/B5HYLZTQ3A5ZQ+4EVn5WHiiwRsOHwcenoVP/Mrq5YtW8IvNAyhoaF4FREB83r1MOvXX6v8N5o4fTr+mDIFL1++RGFhIaytrauki662UFNTw/ELl+Ex0B0jW5ljkEMzKCv+r9s5KTMHuwLCkKCkg/1H5fOoI4vFwrHL1zCkZ3dMyy1ET1PdUt2UmYU8LH+VgAbd+8LDa7xc4gAAMzMznL53H/P+GI/sD+/hwiuAilCI90oqCOMqwWvBYoyU80yY4ydPRl5OLrbs3Am3rDw0U+CKvo9UoQD/KnOR06w5Tt+4LteZD+Vp6dKlePLkSblzt4tDX1+fscfWcnJy8OHDB9G/o6KiEBYWBh0dHZiZmaFPnz5Ys2YNzMzM0KJFC4SGhmLz5s0YO3asaJ+ZM2fCw8MDbdq0gZOTE/bv34/Y2FhMmDCBkRglIfFMcdeuXcOIESOQm5sLDQ2NEn+ALBYLX78yN4r7e+Xdj/D19RX7+XemZ9t68eIFZozzxGTnFujdqhEUfujKTs/Nh2/gSzxJKcSxcxfk1qAQQnB47x6c3r8XThoc/KKjDCUFNuJzi3AmOQ/cBqZYsWVHrZ8usaaqjTPFFcvPz8fJY0fx9/Ej0FPiQENJEck5eeBq6mCs91T06NlT7vcCc3JysGHFUjz+5zZ66CjBQomFIkIQkCVAvIIa/pw9F33cq+42SVJSEh4+fIiC/HxYNWwIJyenKr0fGhUVhZ3r1uHpv/egIBCAsNnQt7DAlCWL4eLiUuNmOqzNM8U9ePAAXbt2LbV99OjROHLkCLKzs7FkyRJcunQJycnJMDIywrBhw7B06dISPQS7d+/Ghg0bkJCQABsbG2zZsgWdO3cut9waM/VrkyZN0KtXL6xduxaqqqoSFVbd5HFQTE9Px5GDB3Djwt+wN9aFsYYKeEKC10kZSBNyMHqCN/r261cl3byEEDy4fx/PHvojPzcX+kbGGDh0GAwNDeVe9s+sNjfoxQghyMjIQF5eHrS1tavlb5vH4+HevXuI//wZikpKsLO3/ylXcKxqVd2gf/r0CV27dqVzudeEBl1NTQ0vX76ElZWVRAXVBPI8KAqFQoSHhyM5ORlcLheWlpawsLBgtAyqZqoLDTr186rqBp3D4Ui02loxY2NjnD9/Hu3bM/ekUHWRV4Mu8WVjjx49EBQUVCsbdHlis9lo3bp1dYdBURRV4zk5OeH+/fsYNGhQheuhA9/umdP10MUjcYPeu3dvzJkzB69fv0bLli3B5ZZ8frOvnJc4pCiKomq/xo0bIywsDOHh4Vi+fDmeP38umlWu+FG3tm3bYtmyZWjVqlV1h1srSNygjx//baTpypWlFwdgsVhVOv0rRVEUVbu1bNkSy5Ytw4MHD3D//n1kZWVBU1MTXbt2RZcuXdCyZcvqDrHWkLhBZ2rqPoqiKOrnxefzsW3bNuzbtw/p6elIS0sr8Qz+1atXoaurC21tbfz555+YNm0anUOiErXzYUaKoiiq1nr16hVsbW2xePFivH//HqmpqaUm1CGEIDU1Fe/fv8fixYvRunVrvJLz4k61nVSnO7m5ufD390dsbGypJeym1oJ5simKoqjqce/ePYwcORIJCQli71NQUIBXr16he/fuOHHiBLp16ybHCGsviRv00NBQ9OrVC3l5ecjNzYWOjg5SU1OhqqqK+vXr0wadoiiKKtOrV68kbsy/l5CQgJEjR+Lu3bt0joIySNzlPmPGDPTp0wdfv36FiooKnj59ipiYGDg4OGDTpk3yiJGiKIqq5fh8PoYNGyZ1Y14sISEBgwcPrtHrwVcXiRv0sLAwzJo1S/RYQWFhIUxNTbFhwwYsXLhQHjFSFEVRtdyZM2fw6dMnRvL6+PEjtm3bxkhedYnEDTqX+78FAwwMDBAbGwvg2yIpxf9PURRFUcUIIbh48SIKCgoYya+goAD79u2rcGU6cfj4+MDR0REaGhqoX78+3N3d8fbt23LTslgsTJ8+vdR7u3fvFs365uDggIcPH8oUl7QkbtDt7OwQFBQEAOjatSuWLl2KkydPYvr06fR5QYqiKKqU8PBwZGdXvkyuJNLT0xEeHi5THv7+/vD29sbTp0/h5+cHPp8PV1dX5Obmlkj3/Plz7N+/v8wJbs6ePYvp06dj0aJFCA0NRadOneDm5lYtF7gSN+hr165FgwYNAACrVq2Crq4uJk6ciOTkZOzfL59lFimKoqja6/Hjx8jMzGQ0z7S0NDx69EimPG7fvg1PT0+0aNECtra28PX1RWxsLIKDg0VpcnJyMGLECBw4cADa2tql8ti8eTO8vLwwbtw4NG/eHFu3boWpqSn27NkjU2zSkLhBb9OmjWi5OX19fdy8eRNZWVkICQmBra0t4wFSFEVRtdujR49k7h7/ESFE5gb9R8UnHTo6OqJt3t7e6N27N3799ddS6YuKihAcHAxXV9cS211dXfHkyRNGYxMHnXaHoiiKkqsfu7BrYr6EEMycORMdO3aEjY0NgG8D+UJCQvD8+fMy90lNTYVAIICBgUGJ7QYGBkhMTGQsNnFJfIWelJQEDw8PGBkZQUFBQTTavfhFURRFUd9TU1Or8flOnjwZ4eHhOH36NAAgLi4O06ZNw4kTJ8pdFrZY8UDxYoSQUtuqgsRX6J6enoiNjcWSJUvQoEGDagmaoiiKqj06duyIc+fOMdrtzmKx0LFjR0bymjJlCq5evYqAgACYmJgAAIKDg5GcnAwHBwdROoFAgICAAOzcuROFhYXQ09MDh8MpdTWenJxc6qq9KkjcoD969AgPHz6ka3/XYEKhEDweD0pKStUdCkVRFJydnaGlpYWMjAzG8tTV1ZW5QSeEYMqUKbh06RIePHgAS0tL0Xu//PILXr58WSL9mDFj0KxZM8ybN0/UK+3g4AA/Pz/0799flM7Pzw/9+vWTKTZpSNygm5qaMj64obb7/Pkz9u/djZBnz8BiscBmswAWG30HDMSw4SOgqqpaNTHs3I5A/3tQ4bDB5bBRyBeCraKGUX9ORD/3/qXWrqcoquYihCAnJwcqKiq1fpWxVq1aQUNDg9EGXVtbW+Z10r29vXHq1ClcuXIFGhoaoittLS0taGhoiO6lF1NTU4Ourm6J7TNnzoSHhwfatGkDJycn7N+/H7GxsZgwYYJMsUlD4lqydetWzJ8/H/v27YOFhYUcQqo9oqOjMX/WTLAFhRjv3hPLhi4V3YLILyjE33ceYMBvPWHr4IiVq9fK5Yo5MzMTU8ePBf9rEsa1bYqlf/YtcRskM68Ax2+chtumdRg9YTI8xoxlPIayxMfHIzU1FcrKyjA3N6e9BVSFhEIhbt+6hfMnjiEtLRWKXC6aWLfAuEmTS1w11XUCgQDXr1zBoU0bUZiSDDU2G4VCgjxFRfQZMQJjJ3mjXr161R2mxFgsFgYMGIB9+/YxMrmMsrIy/vzzT5lv+RY/WtalS5cS2319feHp6SlWHkOGDEFaWhpWrlyJhIQE2NjY4ObNmzA3N5cpNmmwiBiX29ra2iW+uNzcXPD5fKiqqpa66vv69SvzUTIkKysLWlpayMzMhKampkx5hYaGYvZUb+xbNA1WpkYVpr1y/zEOXb+H0+cuQENDQ6Zyv5ecnIzh7n2wqrsd2loZV5hWKBRi7uUA6Ns5Y+HylYzF8L2ioiL8ffokTu7dDUNhIQyVFVAgJIjIKoRdJxdMnDW3Sg/OPB4PsbGx4PF4MDY2ZvS7/x6T9ao6yigoKMC5v//Gv//cRl5eLnT19TFk+Ei4uLhUyRgZ3wP7cOLgfvzSqAFGtGmGBvU0wOMLEBKTgAP/RSJXQRXrd+xGo0aN5B7LmzdvsGfTenx8/QogBIoqqhjs9QcGDBoERUVFuZYdFhaGqcOGogu/EIOUFKCt8L9BxnxC4JdbgHNQQH/vyZg4YwZj5cpatwoKChAVFSWaKa0sAoEAz58/h5eXF16/fi1ryGjRogXCwsJqbc9FRd+ZLL+HWA360aNHxc5w9OjREgVQlZg6KEZHR8PLYzjOrl8EHS3x8nkU8hJbz93E3xcvM1IJ8/Pz4d7jV2zqaQ9r4/pi7zfvcgCa9RiAcRMmyhzD99LS0jCiTy/0UeVjhKUe1Ln/+4yEEDxNyoDP+zSMX7oK/QcNZrTsH6WmpmLbmtV4eOMGmrBZUGARRAsI9Js1x6zVa2TupvtRbW7Q9+zaiYt/n8GgXzuir0sHaKipIj45Fcdv/IvAiLdYsXYdOnTowFh5P1oybw6EH19iWW8ncNhlP3QTl5aJcafvYuN+X9jZ2ckljuzsbPw5fAhUkz/jTzNN2OlrAQCying4GZ2Gi0l5WLBhM1zd3ORSftDz55g3ZDC2qHKgU8HxQUgINubyYDxsBOavWsVI2VXVoIeGhkJRURE9e/aUaYGWBg0a1PrV1qq1Qa8rmDooDh/8O1aM+R0NzSq+Kv7R7jNXoNHQBqPF7MqpyK7tW6EZGYjh7W0qT/wdoVCI3nuv4NK9h4w98pGfnw/3bi5Ya6YMW93yr4J5AiE8n0VjnM8WdO/Zk5GyfxQVFYXRbj0xSVAAZ1XlEleYUYVF8CkUYpzPOgwYMpSxMmtrg7529SrkxUdjxaTRZV6JZ+XkwmPxesxZshydO7swUub3Du7dg5h7V7G8d+UnDF9z8jD0yG2cvvEP6tcX/wRWHPn5+Rjwa1fMM+Cgo2G9stPwBRj7LAZeazahZ+/ejJafnZ2NXvZ22KPEQj2Fyh/9JYRgcU4hhu/YhR69ZI+lKht0Ozs7+Pv7S72EaoMGDerEeujyatAlfg4d+NYovHv3Do8ePUJAQECJlzwFBASgT58+MDIyAovFwuXLl+VaXlni4+MhLMiTuDEHAM9+PXDmxDGZYyCE4NLpU/i9TTOJ92Wz2Rhh3winjsseR7EDu3bAQ4tU2JgDAJfDxkFHc6ybPwdCoZCx8ovx+XyM6fMbNrL56KimUqqRslRSxC4NJRxasAARERGMl1+b/Pfff/gYHlJuYw4AmupqOLl2PpYtmM/YohrF+Hw+Th8+gKVu7cVKr6OuijldbbFv53ZG4wCAdcsWY7w2KbcxBwAVBQ5825pj/bxZyM/PZ7T84wcPYijhidWYA9/uR89W4WLX6tWMxlFVunXrhrt376JFixaVPt9dTEVFBS1atMDdu3drfWMuTxI36E+fPkWjRo3QvHlzdO7cGV26dBG9iqeElZfc3FzY2tpi586dci2nIgf27cU4d9fKE5ZBVUUZTU0bICQkRKYYAgIC0N5EF4pSdt3/bt8Mfx8/wsjTCoQQXD15AgPN9cRKr6LAQWctLv69e1fmsn905eJFdC3Ig7Fi+aP5uSwW5iqysGXZUsbLr032bN+GhV5DK71Hrq6qimE9XXDu778ZLf/6tWtwa2YKdjnd7GX5pbklHty+yeg62DweD4//uYU+prqVplVW4GCEsTrOnjzBWPmEEJw/fAg9VSUbNKqtwIFGago+fPjAWCxVydraGgsWLICmpmaldYDNZkNDQwMLFiyo1d3sVUHiBn3ChAlo06YNIiIi8PXrV6Snp4te8h4Q5+bmhtWrV2PAgAFyLacizwIfo2tbe6n3d+/SHv/cuilTDHdvXENfGwup91dW5MJAhYv09HSZ4gCAkJAQOKhzwOWIX5XGWGjjxB7mT8qOb9+G31UqP8lpqKyIL+HhcpuOsqbLzc3F15QkWJpUPJiz2LCe3XD+zClGYzh3zBcebZtLtA+bzUZnqwZ4+vQpY3H4+fmhp46y2IP/Bpvp4cLRw4yV/+nTJ1jyCqEkwYlNsb6CQlw4fpyxWKpKSkoKfv31V0yePBnJycmV9tYJhUIkJydj8uTJ6N69O1JSUqoo0tpH4ku89+/f4/z581Uy4lRWhYWFKCwsFP07KytL5jzZLJZMI3/1tOshPfyTTDGkp6VBt37pVX8koaumgvT09BKLEEgjISEB5kqSfR8NVJWQ9pH5P8qirCxoiTn9sCmHjcTERDRs2JDxOJggj7pbLCUlBWaG+mKnV1NVgVAgYKx8AMjKyoSehuRjOEw0lJGcnMxYHLGfPqKxiviNqSqXA1LI3O2H1NRU6BMhAMmnzdbnKuB5/BfGYmGSUCgs0QMo+P/6Ex0dDVdXV3z6JPkxMCMjA3fv3kX79u1x7969anksrKaT+LSwXbt2taabx8fHB1paWqKXqalpdYcEHo8v8+MvXEUueALZ7kHzBEJGHsPhcrngEckadAKALcEVvdj5SnCixQOR+2NIspBn3eVyueDxJWugmX56jcViS3XLhydk9ndTVFYGTyhZHCwprqbLw+VywYd0Xy6fECjW0PkdEhMTERoaKnqFh4cjPT0d3bt3l6ox/96nT5/QrVs3pKamMhRt3SFxzZwyZQpmzZqFI0eOIDg4GOHh4SVeNcmCBQuQmZkpesXFxcmcpwJXETl5eVLvH/UlAQ2MTWSKoYGJGWLSMmTK40tGtsxX5wDQvHlzBGcXSbRPUHImmrdkfqldkyZN8K6gsNJ0QkIQRVgwMhKvy7k6yKPuFjMwMMDHz/FiN6jRXxKgoyv+Fb04LBs1QsRnya+0w5MyGO0dtHNog4fZ4p/cxGbno55BA8bKNzU1xScpG/R3AgKrFi0Yi4VJhoaGsLOzE71atWqFRYsWISoqipH8P336hGHDhjGSV10icYM+cOBAREZGYuzYsXB0dETr1q1hZ2cn+m9NoqSkBE1NzRIvWQ0cMgynb92Xev9T//hj0OAhMsUwZKQHToRI30vyJT0Lqrr1GXlszczMDLmaekjJr7whLbb/czb+mDFL5rJ/NHnxEhwTVH5wvJ9XgB6DBtfo1QHlUXeLKSgooGOXbrj/TLzBmfsv3MSfk6cwVj4AjJ88DfsDX0m0T3Z+IaJzeGjWTPKnO8pjZ2eHN3wOcnniDbQ7EP0Vf8yex1j5+vr6YBuZIFnM8r93jc3FkJEejMXCJDabXWIVzvPnz+PNmzeMlhEUFIQzZ84wmmdtJ3GDHhUVVer16dMn0X/rukGDB+P8v4+k6i6M/pIAVS1tmZ+jNTc3R4GSOpKzcqTa/+CTCIyfNlOmGL73x6y5WP8mSay0r79mI7defbncu7a1tQWntT2u5ZV/chFVWARfRTVMmj2b8fJrkwmTvLHO9xyycioeGBj25j0iPyehfXvxHi8Tl42NDWLyBEjNFn9gom/gS4zwGs9oHADwx8w5WP6q8meiI9Nz8IIoM7bCl6j8+fNxukiyWyCR+YWwsHeQ2+yHTFu9ejWys7MZzTMjIwOrGJpcp66QuEE3Nzev8CVPOTk5CAsLQ1hYGIBvJxdhYWGIjY2Va7nfU1JSglOnzjh3x1+i/QghWLHvBCZNnc5IHH9Mm4l1d55LvF9SZg6exKUx+ohhDzc3qLTtgo2RCRWe6LxJz8H0N1+x89hJxsr+0d5TpxFi54hFuTxEftdrkMrjY3duIVYoa+LkHb9aOR82kwwNDbF6418YNHc13kaV/vshhOCGfyDm7TiKw8dOyGUK2DVbtmP08TvIEeM2yf030XiUWoghw4YzHsfAIUOh27U35r/4jMJyBv89S87E9LfpOHz+MuPfxa/du+NtA1M8LxDv1lWWQIDVfBYWrFvPaBzyUrwMqTwkJyfL9Bjwnj170KpVK1EvmJOTE27dulUize7du0UTwDg4OODhw4el8hEnTVWQanTH8ePH4ezsDCMjI8TExAD4tmjLlStXGA3uR0FBQaJ7MsC3VW7s7OywdGnVPlO8ZNkKnL3/FPf+E68iEUKwZJcvWnfozNiVTndXV6g0boXd/qFi75ORmw/PE3ew4/BRxg9Ka7duB7tLHwx4Go3LMSngf/coyruMHMx+8QULvvBx6vZdua4TzOVyceDs35hz6QouOrTHeJYyxkMRawxM0XHLDtwJDoGxseSTAtVF7du3x+6Dvvjrwh24z1iOXacv4+iV21h36DR6TFqAoIQsXLx2Hbq6lT+jLY3WrVtj8aZt+P3QDTz9EFfmyWBeYRF2PwjB7rDPOPb3BbnN3b14jQ/aTJgF9+BELH4Zj3ufU/Eo4StOfEiEe2A0jquY42+/+zA0NGS8bDabjZM3bmCflh7+zat4BP2XIh4m5Qmw8eSpWrM41qlTp5CWliaXvFNTU3HqlPSPVJqYmGDdunUICgpCUFAQunXrhn79+uHVq2+3g86ePYvp06dj0aJFCA0NRadOneDm5lbiIlKcNFVF4qlf9+zZg6VLl2L69OlYs2YNIiIiYGVlhSNHjuDo0aO4f1/6+8vyxuT0mXl5eRjjMRJtG5vAq38vaKqXfT/6U1w8Vu4/AfuOXTB9JrP3jYVCIeZOnwrO53dY4NoWGirlj3h9EZuIOVcfw2fXfrRt25bROL6XkZGBI/v24s7lC2ALBWCx2TAws8DEuQvg4OAgt3KrU22d+vV76enpCAwMRF5eHvT09ODs7Fxly+3GxsZi518bEfr0MXo2NYWRuhIK+UKEJqbjbUYBho4ei5GjR1fJQhyEEDx58gTPHz1EQV4uGphboP/vg+T2u36voKAAi6ZORdiDe+gj5KGHiiLU2WzwCBCaX4DTLC6IkQl89u9HkyZNGCtX3lO/Ojk5MTp3wI/at2+PwMBAxvLT0dHBxo0b4eXlhXbt2sHe3l60KhvwbSCwu7s7fHx8AECsND+qMXO5W1tbY+3atXB3d4eGhgZevHgBKysrREREoEuXLjX6UQKmD4oCgQB/nz2Lk0d9YaqvjQFdO0CvnhZ4fD6i4xNx+k4A6unVx6Sp0+Ho6MjAJyjbxfPncGjXDpircuDVrjmaGOpCiauAjLwC3Hn1CSdDP6KhTSvMXbIcZmZmcovjZ1UXGvSaoKCgAA8ePEBKcjKUVVTQpEkT2Noy/zRETZeXl4dTR47gzoXzyM3JAVdRETb2Dvhz9my5PHor7wa9adOmePfuHROhlqlJkyZ4+/atzPkIBAKcO3cOo0ePRmhoKBo1agRVVVWcO3cO/fv3F6WbNm0awsLC4O/vj6KiokrTlEVeDbrEp7xRUVFljmZXUlL66Wbe4nA4GDZ8OIYNH46IiAjcvnkD6e8jweUqwtDICAeOn4aennhTospiwO+DMOD3QYiIiIDv3l34EhSC/IIC1NPSQnuXLji34RDU1dXlHgdFyUJZWRk95bRoT22iqqqKcZMmYdykSdUdCiPkvf6XrPm/fPkSTk5OKCgogLq6Oi5dugRra2vEx8dDIBCUukVoYGCAxMREAN+6/CtLU5UkbtAtLS0RFhZWagDcrVu3fup5dm1sbGBjI9nKZ/KI4a+deypPSFEUVUXkMaCSyfybNm2KsLAwZGRk4MKFCxg9ejT8/f1FA2d/zJ8QUmqbOGmqgsQN+pw5c+Dt7Y2CggIQQvDs2TOcPn0aPj4+OHjwoDxipCiKomopJiawkmf+ioqKosmK2rRpg+fPn2Pbtm3YsWMHOBxOqSvt5ORk0RW5np5epWmqksSj3MeMGYNly5Zh7ty5yMvLw/Dhw7F3715s27YNQ4cyt8Y0RVEUVft16FD5eveycHZ2ZjQ/QggKCwuhqKgIBwcH+Pn5lXjfz89P9JnESVOVpBo2On78eIwfPx6pqakQCoUyT5RCURRF1U3Dhw/H0aNH5fLomp6eHoYPl35ugoULF8LNzQ2mpqbIzs7GmTNn8ODBA9y+fRvAt0ejPTw80KZNGzg5OWH//v2IjY3FhAkTRHmIk6aqyPQcSFUM+KIoiqJqLwcHB9SvX18uDXr9+vVhby/9ctZJSUnw8PBAQkICtLS00KpVK9y+fRvdu3cHAAwZMgRpaWlYuXIlEhISYGNjg5s3b5YYQyZOmqoi8WNrtdnP8OgPVfXoY2tUbSbvx9aAb5PLTJgwgdHpX+vVq4e9e/diyBDZ1saoDvJ6bI35NSwpiqIo6jtDhgxhdFEd4NsAttrYmMsTbdApiqIouVuzZg0sLS0ZycvKygqnT59mJK+6hDboFEVRlNxpa2vDz88PVlZWMuVjZWWFe/fu0TFcZZBqUNzkyZOxcuVKuT9fSImvoKAA4eHhCAkOQmpKCvg8HlRUVdGoSVO0adMGZmZm1TLRAUVRVDELCws8ffoUw4YNQ3BwMDIyMsTet169emjTpg1On66aGThrI7Gv0D9//iz6/1OnTiEn59ta3C1btkRcXBzzkVGVKioqwpnTp9GnpyuGuv+GG8cPwlCQiV8aG6KXjTmcTLTwNTIIPgvnoEdXF0yeOAGvX7+u7rApiqqDxB1fra+vj7t372LPnj2wtrautHHW09ODtbU19u7dCz8/vzrRmMtrLLrYV+jNmjWDrq4unJ2dUVBQgLi4OJiZmSE6Oho8Hk8uwVFlI4Rg/969OHf6BPp37YATK2dBQ021zLQd7VvB6//XDHjx5gO2rV6K5Kw8rN+8ldEVmyiK+jlxOBwA3y4wVFRUxN5v6NChGDp0KIKDg3H69Gk8fvwYX79+FU2bqqOjA2dnZwwfPlymR9Nqory8PABgfEVDsRv0zMxMBAcH4+HDh7h48SJ69eoFAwMDFBYW4p9//kH//v3lslZwbVFUVITIyEhkZGSAzWbDyMgIVlZWjHdzx8TEYOqkCehi2xS3dq4R/TGJw7ZZI+xZNA2xCUmYNmUiXLr3xLQZMyXKoyLZ2dm4f/8+ggMf4dWLFygoKACLzYKJqRkcnDqik4sLmjZtykhZFEXVDAoKClBVVUVKSgq4XC7Y7NIdvwKBAMC3W4M/Hm9atGiB1atXV1hGQUHF68TXFoQQ5OXlITk5GfXq1WPs2FtM7OfQCwoKRM/LaWtrIzg4GAkJCfj1119hY2OD169fw8TEhJFl7OSF6Wd5MzIycOzoUfzzz21wFRRg3bQpdHTqQSgUIjbuC6JiYqCqpoaRIz3Q+7ffZF7P+dmzZ1g4azp2LZiMxuayLaNICMG+89fx8NUnHDlxEkpK5a+lXpn3799ji88aRL+JQK9mpnAwrY+WJgZQUeSCEIKY1AyExCTg30+JiM3lY/SfEzF46LA6c0+fPodO1WZM1K2ioiJERUVBKBSW+b5QKERcXBxMTU3LbPB/NvXq1YOhoWGZx8AqWT5VU1MTdnZ2cHZ2RlFREfLy8uDs7AwFBQWcPXsWJiYmePbsmUSF11Z8Ph+bNm5EgP8DjBs9ElfOnCi3sf76NR1HTpyC67atWLBgIbq7ukpVZlBQEJbMnYW/NyxGPU0NWcIH8G11oAmD+sCkfiA8hg3Fqb/PSXzCIRAI8Nc6Hzy5dQXLe7ZDS5d+ZZZjoa8NC31tDGhjjez8Quy7cRruhw9h+8HD1TKbEvU/ubm5uHXzJp4/f4Z3795BIBBARUUFrVrZooOzM1xcXH6aA/DXr19x4/p1BD0OQNSnjyBCAk1NTbRu2w4uv3SHo6Oj3E9CCwsLceXSRTzxu4MPbyLBEgpAWCzoGRqiTScXDBw6HA0aNJBrDNJQVFRE48aNUVRUVOb7OTk56N27N4KCgn76pZy5XC7jV+bFxL5CT01NRWBgIJ48eYLNmzeDxWLB0dERz549w8mTJ9GvXz/G7wcwjYkz0bi4OIwf54VhA/tj1AjxrzJzc3OxcPkqCMDGlq1bJfquUlJSMKR/X5zbsATaWrI35j/6+58HeBabgs1bt4u9T05ODjx+74/e5trwdLKR+ED3ISkNU877Y/7ajej266+Shiw2Pp8PPp9f7gxWTKiNV+gZGRlYtXIFXr96BfffesGprSOsmzeDgoICcnNzERb+EvcDHuH+w0cYOPB3TJg4Ua4N+4sXL7B31w58iY0FEQoBFgAWG9179sLoMWOgpaUlt7K/fPmCJXNm4WtcFPq3MIOjhREaG+iAzWYjIzcfITEJuPP+C8KSMjHOexoGD2O+d6mwsBDrli3Bo1vX4a6vgi766mhcTw3s/y8nKa8Qz5IzcSY5HwpG5li7YzdjJ8O1sf7WZbJ8V1JN/aqtrY2AgABERkZi1KhRMDQ0RFJSEtq2bQt/f39Js6syslaq2NhYeI4ehYM7t8HK0kKqGC5cvoJzV27gxMmTYl8Rjxw6GNMGuMKhhfzuP49fuRljpsxCx44dK02bn5+PQb+5YXb7xujUxEzqMvMKizDiyC3MWrsRLl26Sp3Pj16+fIld69bgU8RLqLIBDpuFfAGBsq4exk6bBbfevRk9Q65tB8S7fn5Yu3YNViych07OFa8IJRAIcPDIMVy99Q927d4DCwsLmcr+HiEEf589i2OHD8KqgT7+HNgL1g3/lz+Px8fVB49x7MY9NDAzx5z5C9G4cWPGygeA40d8cWLPDmzs54wWxhUvMlVQxMOmf4MRmc/Gbt+jjD22Gx4ejhmeIzHBSAXuprqVniy8y8jBrIgkDPaejjF/yr4ASG2rv3VdtTToL168gJmZGTQ0NPDixQuoqqrC39+/Rk/FJ8sXVVBQgN9698LBnVthIeOZ8bmLlxEYHIrNW7ZWmvbSxYsIvnsDK709ZSqzMhlZ2fh97hrcunuv0vvpU/8cj1/VC9G7lewH19zCIgw4cB2nb96Bvr6+THm9efMGs8Z5wlyQjz/NtdBCp2RvRmp+EY5Ef8WdrwWYMHcBBo8YKVN5xWrTAfH8uXO4eP4cDu7aBlXVsp+MKEtUdDS8vKdh3/4DjDSqfD4f0yZ7Q58rxMxRv0O9klgiP0Zj5ub9mLd0Obp1+0Xm8gFgk88afA68h/XunaAgwQlecHQ8Ft4OxplrN2V+hCro+XMsGDMSxxxNoa8i/jgWgZBgQfgXNHAbgDlLlskUQ22qvz+DKp/LPTw8HCYmJgAAc3NzcLlcGBoa1ujGXFbLli7BtIl/yNyYA8CgAe7Izc5CgBi9Gft27cACr2Eyl1mZepoaGPRLR5w/d67CdP4PHqAg5h0jjTkAqCkpYu1v7TFjwh8y5fPk0SNMGdQP+xqpY7udSanGHAD0VBQxu7khbjqZ4f6O9fhrzSqZyqxtgoOCcPrkCRw7sEeixhwALC0scPzAHvz5x3jRHBTSIoRgwvhxaG9liKUTRlXamANA84YWuLBpKbatW4OAgACZygeAi+fPIfqRHzYNcJGoMQcABwsjbOrdFqMHDxSN3pZGamoq5oz1wKl25hI15sC3Xqf1tsaIun4eVy5ckDoGqm6RqkH/fqRiREQETE1lG3Fd071//x5xMTHo08uNsTw3rl6BlStXVDjBwPPnz9HC0gQqytKPQJfEiN7dcOrYkQrTrFu2GOv6Vd4tLwkHCyPo8rLw/PlzqfZ/9+4dlk7wwt/tLGCoWvl3pcBmY7udKWKun8PRA/ulKrO2KSwsxNy5c7Bv+xapn7YwNjLCwlkzsGD+fJli2br5L7RoUA8jeks2dkJVRRnH18zDqiUL8eXLF6nLT01Nxa71a7Ghv4vU98JbmhqgT0N9bPtro9RxzBw3Fuua6UNbSbqxRywWCxtsjbFt+WJ8/fpV6jiouuPnGL4qo717dmPmlEmM5qmpqQnndm3h/+BBuWkO7tuDPwYwdxJRGXVVVVgY6iIyMrLM90NCQtBESxlaqswPMJvUsSX2bNkk1b7zJ/6Bg/bG0FAUv6FisVjYaGuCkzs2M7qkY0118sQJDB80AHp6ujLl82u3LviamoKYmBip9ufxeLhx9TKmDh8g1f7qqqpYNHYI9uzaIdX+ALB53Vos/NUeSlzZHiMd59wKty+cE00SIomXL19CNTEaDvqydT8rK3Aw11ILOzeulykfqm6odQ367t27RWvIOjg44OHDh3ItTyAQ4GX4S7Sxt2M87/FjRuHw4UPlvh8XHS3z8+aS6mJvg8ePHpX53tH9ezC2HbNLIBZrZKCLxKiPKCwslGi/T58+QSM7DSbq4s9QVYzDZmG0sSaOHz4o8b61zdmzZzB88CBG8po0fiz27d0j1b6XLl6Ee+f2Mo0S7+Rgi6ePH5X7iFRFioqK8OzhA7g0lf3WGYvFwnC7hjh1/JjE++7ZsA6TLOrJHAMA/GKsg4Bb18Hn8xnJj6q9alWDfvbsWUyfPh2LFi1CaGgoOnXqBDc3N8TGxsqtzHfv3qFli+ZyydvE2BipKallvpebmwsVxap/DNDBuimCnj0t8733kZGVjgSWRWsTfUREREi0z96/NmK8ifSP8vU308XFY0fkNrdyTZCcnAzD+vUlmpazIh3at0NYWJhU+x73PYSRv8n2mCKLxUJ/l/a4dPGixPsGBwejo2XZE3pIo79dE9y5dlni/aIiI2BdxjgPabBYLDhqKUn8t0PVPbWqQd+8eTO8vLwwbtw4NG/eHFu3boWpqSn27JHuakEcIcHBcGhtK7f862lplrni0OvXr9HCSvpHwqRlbmSIz7Glu1MFAgHYgiK5Tqzh0EAbwc8lm5wo/L8naGdQT+oyFTlsNFVm4+PHj1LnUdMFM1yHWSwWlJWUkJ+fL9F+PB4PLCEfmupqMsfg3s0Zd27flHi/oP8C4WAk222H76krKyE7I12ifdLS0qDLLntGNWnZq7DxPDCQ0Typ2qfWNOhFRUUIDg6G6w8zrbm6uuLJkydl7lNYWIisrKwSL0klJSXBqIH85qhvYGiAlJSUUtuzsrKgrSH7gU9SLBZLNJnF93Jzc6GlrCjXsg211JGSEC/RPlwQmU8yDBXZSE0tu6ekujBRd4vFxcbC0oLZk0MTIyMkJSVJtE96ejr0tOsxUr5uPS1kSDEQLO7TJ1joMRNDMQVCJOrhiYuLg7kKs39L5hrKiPvwjtE8ZcFk/aXEV2sa9NTUVAgEAhgYGJTYbmBggMTExDL38fHxgZaWluglzWh8eXfFslisMuc/Ll5xqKaoii5pFgvlzgVdHibiYkHycuWNibpbTB51icViSfzdC4VCMBUFC5KXDwCEgRPAsnKVKDUhjH0PxViomr9RcTFZfynx1ZoGvdiPf4wVHawWLFiAzMxM0Uuaddv19PSQkpomVaziSElNK3NyCnV1dWTlStalyRShsPSBQU1NDdmF8l0mNyU7Dzr6kt2jF7Bkr8KpPCFjs34xhYm6W6xBgwb4/EWyno/KJCQlSjwRkLa2Nr5mMfNEQUZ2DrTq1ZN4vwYmZviSzuzVooDFlugkoUGDBvhSwOwAti95hTA0qznrIjBZfynx1ZoGXU9PDxwOp9TVeHJycqmr9mJKSkrQ1NQs8ZKUnb09Ql6ESxWzOFLTvkJXt/Q9PWtra7yKku7RIFnEJ6fCwMio1HYFBQXwWBy5XgWEJqTD3rGtRPtYNrfByzTpD9ACIcHLHF6NWxueibpbzN7BAcFhLxiMDsjJzZN4kQ0lJSXkF/GRXyDZkwxlufX4GZw7u0i8n0O79gj+wtwJekERD0pqkg1uMzQ0RCKP2b+jkBwBHDs4M5qnLJisv5T4ak2DrqioCAcHB/j5+ZXY7ufnhw4dKp6PWhbW1tYIC38pl7xTU9OgUc7KaZqamsjJl/3AJ6ng12/hUE6jam7VEJ9SJBsAJInQzymwtZVs8NakeQuwLyZT6jJvf05Dj4GD6vSKYsbGxoiOjQOPx0wPS9iLcDRuLN0J0ODhI/D3nQcyx3Dmjj+GSzF1r6OjIx5GJchcfrFbLz+ii2sPifczsLBEVJbkz6+XhRCCpxkFEv/tUHVPrTqKzZw5EwcPHsThw4cRGRmJGTNmIDY2FhMmyL5AQXkUFBRgZm6OyDfMr/Pue+IkRo70KPd9/fqG+JJUesCcPD0Kew2ncs70h40Zh6PP3sil3C/pWVDVrS/xlKQ2NjaI46jia4HkzyQTQnDoczbGTvSWeN/ahMVioW/ffrh87QYj+e055IuJk6SbaGnosOE46yfb3BHBr96iuY2txHUFAFRVVdGklR1Copm5BXE0+B1Ge42XeL8JcxdgfzQzJ8f/JWWgdUeXStdgoOq+WtWgDxkyBFu3bsXKlSvRunVrBAQE4ObNm3JfU3uS92Rs3b2X0TwLCgpwy+9fuPXqVW6aUV7jcOjybUbLrUhhURFefIhB69aty3y/c+fO+O9zGgqKmL+Xvv/xS/wxfZZU+y7bvBVeQXEoEkg2sG3jmyR0GjhE5gU2aoMxY8dizyFfmedhDwoJRX5hEZo1k26CIVVVVTi274DTt+5JtT+Px8eK/SfgPXWaVPsDwOxFS7H01jMIZBwIeTHkLWydXVBPinv57dq1w3tFLbzLkO33EAgJVn34imkLF8uUD1U31KoGHQAmTZqE6OhoFBYWIjg4GJ07d5Z7mba2tiAsNh4+LvvxOGms8NmAadOmV7iMZ9euXfH4RSR4vKqZAeqCXwAGDhla7gAfFouFKXPnY8Wtsieekdb7xDS8zOShS5cuUu3ftl17/LFiLYY/jUJ2UeXfFSEEPq8TkNbUAbMXL5WqzNpGXV0dixcvwbS5C6QeB5GRkYG5S5aLtUpgRZatXIVLj4Jx92mwRPvx+Xz8sWoLxk6cgkaNGkldvqmpKQaM9sK6fySb8+B7sWkZ2PfsHZasWiPV/iwWC9uPHMf0l4nI50u/wIvP6wQMmTQNxsbGUudB1R21rkGvLhs3/YWla9YhpZyZ3SRx3z8ACckp6OfuXmE6FouFYaNGY/ffV2QuszL5BYU4fNUPIyq4BQAA/foPQLKiFgI/MjNqlccXYMalAGw/cFimx4n69B+AOTsPYGDQF2yITEBKGeMPCgUCnP6UjD5PoqDRcxA27dlXox4NlLduv/wCOwdHTJ+7QOJVwr5+TcdQz3FYv36DzD0aCgoKOHbqDA7fCsChSzfFiiU1PQPD5q9Fz4FDMGDgQJnKB4BxEyYiQ88MW+8FS3yCE5WSDq/T93Dw9N8ydXObmZlh9oatGPVfNPJ4kjfq298lIcu6DSNrolN1A23QxaSlpYXt23dg+NjxMjXqAY8eY9OOPdi9R7wu/DFjveAf/g7vY+T72MeyPUcxc94CsUYub917AMvvvsCrL8kylckXCPDHKT+Mmzmfkdsmzp064W5IOFrPXonJcQIMfhqDqS/iMSs8AWOC4tAvKBG5vT1w/vFzTJ+/4KdqzItNnjIFju07oM+gYXj3/oNY+9y4/Q8GjRqDdes3wLGtZE8hlEdVVRUnz55DlpI2enovwsYjZ5GanlEiDSEET1+8wphlmzBxwz7MXroSw4aPYKR8FouFv3bsBq+RHYb73kRiRuWP0xFC4PvkJSZfewbf85dhYWEhcxyubm6Yunkn3P+LwdMk8QZ3puQXwuO/aOS2/RV/7dn/U9ZjqmwsUpNmI5AzWRaOLxbx8iWmTp2ChbNm4NduXcTeTyAQ4K/tOxEU9hK+R45ATU38WeBiY2MxzmM4Lm1eLpelVO/9F4KTD4Lge+y42PskJydjeP++mNmhOXrYWElcZkpWLrz/vodBE6ZiqBSjlcWRk5ODtLQ08Hg8aGtrQ0dHRy4HPybqVVWXERsbi4UL5kPA48Fj6GC0c2wDXd1vz+ITQhATG4sHAY9w9uJl2NnbY8nSZYzNBf8jgUCA27dv48iBfSgsyAf5/3vbfIEALe3sMWHSZFhZSV7HxBUeHo4ls2dAj8XDcLtGcLAwgsb/r08uFArxPukr/N7E4FpkHHoN+B3TZs+t8FaZNNLT0zF/8kSkRL7EaCN1dDLUguZ3aznwBEKEf83G8S/Z+ARlrNqxGw4ODoyUXRvrb10my3dFG3Qp5OTkYOGCBUhPS8XkP8ehbRuHchuKoqIiXLp6HQePnsCIkSMx2tNTqkblzj//YN/WTTixdj6UFJmbNvK/8NdY5XsO5y5dkegkAwDy8vKwcNYM5EZFYkUvJxhoVX51LxAKcS4oEr4hn7Bux260adNG2tBrjNp8QPzy5QvOnzuHoKDnSE9PB5vFhpAIYWZmhg4dnDFg4ECpRpPXRu/evcOFM6cQ9vwZcrIyv83mxuGgUZOm6Ny9J/r07QsuV74LJqWkpOD4wf14+uA+cr6mgU0EIGCBraKKFq3tMdRrfLmDVqVVm+tvXUQbdDExXak+fvyIfXv3ICw0DGamxrC3bQVdHR0IBALEfv6M0PCXyMzKRt++/TDSw0PmMm9cv4592zfjwJIZ0NepJ3P81/2fYN+Vuzj193loaWlJnc/jR4+wbd0acPOz8LuNOdpYGsNI+3+fNb+Ihxexibj34QsefEpE74GDMHn6TCgyeGJSnegBkarNaP2tWWiDLiZ5VSpCCOLj4xEWFoaM9HRwFBTQoEED2NnZMV55g4ODMW/mdPzRvwd+7y75TFkAkJGVjTlbD0CrgSnW+KxnrCs1NjYWN65eQXDgYyTGfwGLCAEWC1xlFdjat0HHbr+ia9eudW4SF3pApGozWn9rFtqgi6muVKqioiKsWrEMYc/+g1c/V/Tu3F6se3oJKak4dOk2AsJeY8XadXB2rjlTRdZm9IBI1Wa0/tYssnxXCnKKiZIjRUVFrFrjg69fv8L30EG4TV4MKxNDODRrCPtmjWGgqw0FBQ7yCwrxNjoOwZEfEPzmA5RU1TFuojcWb/mlzl0lUxRF/exog16L6ejoYNacuZg5ew7i4uIQFBSEK8+fIS01FTw+DyoqKmjUuCm6DfLAzNatJR70RlEURdUetEGvA1gsFszMzGBmZoYBAwZUdzgURVFUNaD9rhRFURRVB9AGnaIoiqLqANqgUxRFUVQdQBt0iqIoiqoDaINOURRFUXUAbdApiqIoqg6gDTpFURRF1QG0QacoiqKoOuCnmlimeNr6rKysao6EqkuK65M8l0WgdZeSF1p/axZZfo+fqkHPzs4GAJiamlZzJFRdlJ2dLdMytJXlDdC6S8mPPOtvWloaAFp/JZGWlibx7/FTrbYmFAoRHx8PDQ0NsFgsuZSRlZUFU1NTxMXFVduqQjUhhpoSR1XEQAhBdnY2jIyM5Lbozc9Sd2tKHDUhhqqKoyrqb0ZGBrS1tREbGyu3k4a6IjMzE2ZmZkhPT0e9evUk2venukJns9kwMTGpkrI0NTWrfZnAmhBDTYlD3jHI+yD1s9XdmhJHTYihKuKoivpbXE5N+D5rA2lOruigOIqiKIqqA2iDTlEURVF1AG3QGaakpIRly5ZBSUnpp46hpsRRE2KoLWrKd1UT4qgJMdSkOGRVVz5HVZDlu/qpBsVRFEVRVF1Fr9ApiqIoqg6gDTpFURRF1QG0QacoiqKoOoA26BRFURRVB9AGnUG7d++GpaUllJWV4eDggIcPH1Zp+QEBAejTpw+MjIzAYrFw+fLlKi0fAHx8fODo6AgNDQ3Ur18f7u7uePv2bZXH8aPo6Gh4eXnB0tISKioqaNiwIZYtW4aioqLqDq3GoPWX1l95qO56VVswUf9pg86Qs2fPYvr06Vi0aBFCQ0PRqVMnuLm5ITY2tspiyM3Nha2tLXbu3FllZf7I398f3t7eePr0Kfz8/MDn8+Hq6orc3Fy5lBcfHw8+n19pujdv3kAoFGLfvn149eoVtmzZgr1792LhwoVyiau2ofX3G1p/mVUT6lVtwUj9JxQj2rZtSyZMmFBiW7Nmzcj8+fOrJR4A5NKlS9VS9veSk5MJAOLv7y+X/JcvX04MDAzIzJkzSXh4uET7btiwgVhaWsolrtqG1t+y0form5pWr2oLaes/vUJnQFFREYKDg+Hq6lpiu6urK548eVJNUdUMmZmZAAAdHR255D9v3jxs374db9++hb29Pezt7bFt2zakpKSIFZu84qpNaP0tH62/0qP1qurRBp0BqampEAgEMDAwKLHdwMAAiYmJ1RRV9SOEYObMmejYsSNsbGzkUoaysjIGDx6M69ev48uXLxg1ahSOHj0KY2NjuLu749KlS2V2aX78+BE7duzAhAkT5BJXbULrb9lo/ZUNrVdVjzboDPpxWUtCiNyWuqwNJk+ejPDwcJw+fbpKyqtfvz6mT5+OkJAQXLlyBYGBgRgwYAAiIiJKpIuPj0fPnj0xaNAgjBs3rkpiqw1o/S2J1l9m0HpVdWiDzgA9PT1wOJxSZ53Jycmlzk5/FlOmTMHVq1dx//79Klv2Mzs7G76+vujWrRv69OkDGxsbHD16FNbW1qI08fHx6Nq1K5ycnLB///4qiaumo/W3NFp/ZUfrVdWjDToDFBUV4eDgAD8/vxLb/fz80KFDh2qKqnoQQjB58mRcvHgR9+7dg6WlpVzLEwgEuHXrFoYPHw4DAwP4+PigW7du+PTpE/7991+MGjUKioqKAIAvX76gS5cusLe3h6+vr1TrDddFtP7+D62/zKH1qhowODDvp3bmzBnC5XLJoUOHyOvXr8n06dOJmpoaiY6OrrIYsrOzSWhoKAkNDSUAyObNm0loaCiJiYmpshgmTpxItLS0yIMHD0hCQoLolZeXJ5fyVq5cSbS0tMj48ePJ48ePy0335csX0qhRI9KtWzfy+fPnErFRtP4Wo/WXWTWhXtUWTNR/2qAzaNeuXcTc3JwoKioSe3t7uT3qUp779+8TAKVeo0ePrrIYyiofAPH19ZVLeVFRUSQ/P7/SdL6+vuXGRn1D6y+tv/JQ3fWqtmCi/tPlUymKoiiqDqjZN2EoiqIoihILbdApiqIoqg6gDTpFURRF1QG0QacoiqKoOoA26BRFURRVB9AGnaIoiqLqANqgUxRFUVQdQBt0iqIoiqoDaINOURRFUXUAbdCrUUpKCrhcLvLy8sDn86GmpobY2NjqDotxXbp0wfTp06s7DIphtP5SVM1CG/RqFBgYiNatW0NVVRXBwcHQ0dGBmZkZ4+UUFRUxnmd1qCufo66g9VcydeVzUDUXbdCr0ZMnT+Ds7AwAePTokej/K+Lp6Ql3d3esWLEC9evXh6amJv78888SB4suXbpg8uTJmDlzJvT09NC9e3cAgL+/P9q2bQslJSU0aNAA8+fPB5/PL7HflClTMH36dGhra8PAwAD79+9Hbm4uxowZAw0NDTRs2BC3bt0qEVNF+Xp6esLf3x/btm0Di8UCi8VCdHQ0AOD169fo1asX1NXVYWBgAA8PD6Smplb6OZYvXw4zMzMoKSnByMgIU6dOleLbp2RF6y+tv1QNI6+VY6iyxcTEEC0tLaKlpUW4XC5RVlYmWlpaRFFRkSgpKREtLS0yceLEcvcfPXo0UVdXJ0OGDCERERHk+vXrRF9fnyxcuFCUxsXFhairq5M5c+aQN2/ekMjISPL582eiqqpKJk2aRCIjI8mlS5eInp4eWbZsWYn9NDQ0yKpVq8i7d+/IqlWrCJvNJm5ubmT//v3k3bt3ZOLEiURXV5fk5uYSQkil+WZkZBAnJycyfvx40XKPfD6fxMfHEz09PbJgwQISGRlJQkJCSPfu3UnXrl0r/Bznzp0jmpqa5ObNmyQmJob8999/ZP/+/cz+SFS5aP2l9ZequWiDXsV4PB6JiooiL168IFwul4SFhZEPHz4QdXV14u/vT6KiokhKSkq5+48ePZro6OiIDkiEELJnzx6irq5OBAIBIeTbgaR169Yl9lu4cCFp2rQpEQqFom27du0qtV/Hjh1F7/P5fKKmpkY8PDxE2xISEggAEhgYKFG+06ZNKxHPkiVLiKura4ltcXFxBAB5+/ZtuZ/jr7/+Ik2aNCFFRUXlfkeU/ND6+w2tv1RNRLvcq5iCggIsLCzw5s0bODo6wtbWFomJiTAwMEDnzp1hYWEBPT29CvOwtbWFqqqq6N9OTk7IyclBXFycaFubNm1K7BMZGQknJyewWCzRNmdnZ+Tk5ODz58+iba1atRL9P4fDga6uLlq2bCnaZmBgAABITk6WKN8fBQcH4/79+1BXVxe9mjVrBgD4+PFjuZ9j0KBByM/Ph5WVFcaPH49Lly6V6Hal5IvW329o/aVqIoXqDuBn06JFC8TExIDH40EoFEJdXR18Ph98Ph/q6uowNzfHq1evpMr7+4OSmppaifcIISXeL972435cLrdUnt9vK04rFAolyvdHQqEQffr0wfr160u916BBg3I/h6mpKd6+fQs/Pz/cvXsXkyZNwsaNG+Hv718qdop5tP5CtD+tv1RNQ6/Qq9jNmzcRFhYGQ0NDnDhxAmFhYbCxscHWrVsRFhaGmzdvVprHixcvkJ+fL/r306dPoa6uDhMTk3L3sba2xpMnT0QHK+DboCYNDQ0YGxtL/XnEyVdRURECgaDEfvb29nj16hUsLCzQqFGjEq8fD4I/UlFRQd++fbF9+3Y8ePAAgYGBePnypdSfgRIfrb/f0PpL1US0Qa9i5ubmUFdXR1JSEvr16wczMzO8fv0aAwYMQKNGjWBubl5pHkVFRfDy8sLr169x69YtLFu2DJMnTwabXf7POWnSJMTFxWHKlCl48+YNrly5gmXLlmHmzJkV7lcZcfK1sLDAf//9h+joaKSmpkIoFMLb2xtfv37FsGHD8OzZM3z69Al37tzB2LFjSx08v3fkyBEcOnQIERER+PTpE44fPw4VFRWxvjdKdrT+0vpL1Vy0Qa8GDx48gKOjI5SVlfHff//B2NgYRkZGYu//yy+/oHHjxujcuTMGDx6MPn36YPny5RXuY2xsjJs3b+LZs2ewtbXFhAkT4OXlhcWLF8v0WcTJd/bs2eBwOLC2toa+vj5iY2NhZGSEx48fQyAQoEePHrCxscG0adOgpaVV4QG6Xr16OHDgAJydndGqVSv8+++/uHbtGnR1dWX6HJT4aP2l9ZeqmVjk+74mqsbz9PRERkYGLl++XN2hUJTEaP2lKPmhV+gURVEUVQfQBp2iKIqi6gDa5U5RFEVRdQC9QqcoiqKoOoA26BRFURRVB9AGnaIoiqLqANqgUxRFUVQdQBt0iqIoiqoDaINOURRFUXUAbdApiqIoqg6gDTpFURRF1QH/B0qGLn6G51W/AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 550x200 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1,ax2,ax3)= plt.subplots(1, 3,figsize=(5.5, 2),sharey=True,gridspec_kw = {'width_ratios':[1,1,0.5]})\n",
    "\n",
    "cg=(g['p']+g['e'])\n",
    "cc=(c['p']+c['e'])\n",
    "\n",
    "# ax1.scatter(data=g, x=\"p\", y=\"e\",s='frac',edgecolor='k',lw=0.5,c=cg,cmap='afmhot_r',alpha=1,vmin=-3000,vmax=30000)\n",
    "# ax2.scatter(data=c, x=\"p\", y=\"e\",s='frac',edgecolor='k',lw=0.5,c=cc,cmap='afmhot_r',alpha=1,vmin=-3000,vmax=30000)\n",
    "a=ax1.scatter(data=g, x=\"p\", y=\"e\",s=g['frac']*2500,edgecolor='k',lw=0.5,c=cg,cmap='Reds',alpha=1,vmin=0,vmax=6)\n",
    "b=ax2.scatter(data=c, x=\"p\", y=\"e\",s=c['frac']*2500,edgecolor='k',lw=0.5,c=cc,cmap='Reds',alpha=1,vmin=0,vmax=6)\n",
    "#ax2.scatter(data=c, x=\"p\", y=\"e\", s='frac',edgecolor='k',c='frac',cmap='autumn_r',alpha=0.7,vmin=60, vmax=900)\n",
    "\n",
    "for ax in (ax1,ax2):\n",
    "    ax.set_xlim(-0.75,3.75)\n",
    "    ax.set_ylim(-0.75,3.75)\n",
    "    \n",
    "    ax.set_xlabel('# promoters')\n",
    "    \n",
    "    ax.set_xticks([0,1,2,3])\n",
    "    ax.set_yticks([0,1,2,3])\n",
    "    ax.set_xticklabels(['0','1','2','>2'])\n",
    "    ax.set_yticklabels(['0','1','2','>2'])\n",
    "\n",
    "ax1.set_ylabel('# enhancers')\n",
    "ax1.set_title('all MCD, n=2105')\n",
    "ax2.set_title('cyto MCD, n=698')\n",
    "\n",
    "handles, labels = b.legend_elements(prop=\"sizes\", alpha=1,num=5,color='k')\n",
    "legend2 = ax3.legend(handles, labels, loc=\"upper right\", title=\"Sizes\")\n",
    "\n",
    "\n",
    "#plt.savefig('.pdf',dpi=300,bbox_inches='tight')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "26517a4e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.19"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}