Epistasis_pipeline.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8af44c52-46fe-46d2-a808-1ab16123b5c5",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5180d942-fbac-45c5-8e9c-5ced5509fb46",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from src.utils.tree import SNPTreeParser\n",
    "from src.utils.analysis import EpistasisFinder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9bd9274f-5823-474e-84fc-05cebe048f8a",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "bfile = 'path_to_your_genotype' # prefix for PLINK bfile (\"https://www.cog-genomics.org/plink/1.9/input\")\n",
    "ont = 'path_to_ontology_file.txt'\n",
    "snp2gene = 'path_to_snp2gene_file.txt'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e0c521f7-d5de-494f-9f12-87b06d21e0d8",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2227 Systems are queried\n",
      "963 Genes are queried\n",
      "Total 9646 Gene-System interactions are queried\n",
      "Building descendant dict\n",
      "Subtree types:  ['default']\n"
     ]
    }
   ],
   "source": [
    "tree_parser = SNPTreeParser(ont, snp2gene, sys_annot_file='GO_files/goID_2_name.tab')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1c81bdd3-3adf-4ebe-a37e-95287eb5346c",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "attention_result = 'path_to_attention_result_from_your_G2PT_prediction'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2e2b3a9b-bf56-4b2f-9140-1c5965e69e4e",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "cov = 'path_to_covariate_file' # PLINK Covar file https://www.cog-genomics.org/plink/1.9/input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e811636f-0edc-40c0-b73e-8a82f279e676",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Swapping Ref and Alt!\n",
      "From PLINK 4019 variants with 317007 samples are queried\n"
     ]
    }
   ],
   "source": [
    "epistasis_finder = EpistasisFinder(tree_parser, bfile, attention_results=attention_result, cov=cov, flip=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2a2de4d0-7600-45e5-a46e-2c03c0032817",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "target_system = 'GO:0015721'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05f7b3f2-fc31-4f3c-be6a-e6847d237481",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# 1. Epistasis Search in Target System"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a8472a36-b9a9-4669-b9c6-8135d7301775",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "System: GO:0015721, Sex: 0\n",
      "Check Inheritance\n",
      "Running Chi-Square Test...\n",
      "\tTesting 22 SNPs on 17172 risky individuals\n",
      "\tFrom 22 SNPs, 22 SNPs pass Chi-Square test\n",
      "Running Fisher\n",
      "\tFrom 231.0 significant pairs, 98 pairs pass Fisher test\n",
      "Filtering Close SNPs\n",
      "\tFrom 98 pairs, close 10 SNP pairs are removed\n",
      "Calculating statistical Interaction p-value \n",
      "\tTesting 21 SNPs on 171712 individuals, SNPs in system ()\n",
      "\tFrom 88 pairs, 9 significant interaction are queried\n"
     ]
    }
   ],
   "source": [
    "# set verbose=1 if you want to detailed statistical result (not recommended for large system)\n",
    "epistasis_results, snp_inheritance = epistasis_finder.search_epistasis_on_system(target_system, sex=0, quantile=0.9, verbose=0) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8422f8a8-23f6-488f-aa48-41459060685a",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12:21391352:G:A SLCO1B1 1:27215079:T:C NR0B2 0.0023868051398129877 0.044946051545104476\n",
      "12:21352315:A:G SLCO1B1 1:27215079:T:C NR0B2 0.00020210318800223178 0.008892540272098199\n",
      "12:21391608:A:G SLCO1B1 1:27215079:T:C NR0B2 0.002553752928699118 0.044946051545104476\n",
      "12:21331549:T:C SLCO1B1 1:27215079:T:C NR0B2 0.0006015898274226132 0.01764663493772999\n",
      "12:21391352:G:A SLCO1B1 1:27234682:G:A NR0B2 0.00463052918672207 0.048755832662880416\n",
      "12:21352315:A:G SLCO1B1 1:27234682:G:A NR0B2 0.004207345934138964 0.048755832662880416\n",
      "12:21391608:A:G SLCO1B1 1:27234682:G:A NR0B2 0.004986391976885498 0.048755832662880416\n",
      "12:21352541:A:G SLCO1B1 1:27215079:T:C NR0B2 0.00017240908154806815 0.008892540272098199\n",
      "12:21352541:A:G SLCO1B1 1:27234682:G:A NR0B2 0.0034931002245380434 0.048755832662880416\n"
     ]
    }
   ],
   "source": [
    "epistasis_results_with_genes = []\n",
    "\n",
    "for snp_1, snp_2, p_val, p_val_adjusted in epistasis_results:\n",
    "    gene1 = [gene for gene in tree_parser.snp2gene[snp_1] if gene in tree_parser.sys2gene_full[target_system]]\n",
    "    gene2 = [gene for gene in tree_parser.snp2gene[snp_2] if gene in tree_parser.sys2gene_full[target_system]]\n",
    "    gene_product_list = [(x, y) for x in gene1 for y in gene2]\n",
    "    for g1, g2 in gene_product_list:\n",
    "        epistasis_results_with_genes.append((snp_1, g1,  snp_2, g2, p_val, p_val_adjusted))\n",
    "        print(snp_1, g1,  snp_2, g2, p_val, p_val_adjusted)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1060a75-85e9-4b20-94a8-5d3a416676a2",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# 2. Epistasis Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "928fd8f6-06b2-4912-b396-ac7b803062ce",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 2.1 Epistatic interaction plots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9955558a-0d70-4e65-8d5b-1e73e35b1f96",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "put SNP pairs from your epistatic results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d73cb49d-48e0-4df7-a1ad-806f1d164c7d",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2200x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "epistasis_finder.draw_epistasis('12:21331549:T:C', '1:27215079:T:C', phenotype='PHENOTYPE', sex=0) # put out_dir='path_to_save' to save figure as svg"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "135b1712-66ec-46af-93d3-426af1a857c4",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 2.2 Epistatic Sub-hierarchy Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b04678f5-bb01-40e7-aba8-ea3c5c1f9224",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "You can visualize epistasis under the target system"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9e3b9fd4-12e5-4e20-90a2-9b06f8844bca",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from src.utils.visualization.epistasis import EpistasisVisualizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "986a401b-ca46-4103-99f9-0fd992077ae4",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "epistasis_visualizer = EpistasisVisualizer(tree_parser)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7ecce81c-3f12-42a9-bdcb-6076120b0992",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "epistasis_results_genes = [[gene1, gene2] for snp1, gene1, snp2, gene2, p_val, adjusted_p_val in epistasis_results_with_genes]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "47b2a67b-8f41-48a5-8ea1-41baf26eeff4",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
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       "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
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       "<!-- NR0B2 -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>NR0B2</title>\n",
       "<ellipse fill=\"lightgray\" stroke=\"black\" cx=\"165\" cy=\"-90\" rx=\"37.89\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"165\" y=\"-86.3\" font-family=\"Times,serif\" font-size=\"14.00\">NR0B2</text>\n",
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       "<title>GO:0015721</title>\n",
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       "<title>NR0B2&#45;&gt;GO:0015721</title>\n",
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       "<title>SLCO1B1</title>\n",
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       "<title>SLCO1B1&#45;&gt;GO:0015721</title>\n",
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      "text/plain": [
       "<AGraph <Swig Object of type 'Agraph_t *' at 0x1554616c8d20>>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "epistasis_visualizer.visualize_epistasis(target_system=target_system, epistatic_interactions=epistasis_results_genes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "302cea31-ab6a-428d-b607-6a485a168636",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# 3. Epistasis Analysis Result using LLM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "754ee613-0b6f-49a7-a036-fabe2747fb33",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from src.utils.analysis.llm_explainer import EpistaticInteractionExplainer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "527394b9-d35f-434c-8ec0-b950c2897ba9",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "OPENAI_API_KEY = 'your_open_ai_api_key'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "1885e648-d638-4f22-bae7-8aec61b6166c",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "epistasis_explainer = EpistaticInteractionExplainer(OPENAI_API_KEY, model='chatgpt-4o-latest')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1737e7e-f626-43d5-8237-b98d8ffb2006",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Put your target system, phenotype, and target genes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f97bf309-00d1-47f5-80bf-c637bc398f9d",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "llm_result = epistasis_explainer.explain_epistasis(tree_parser.sys_annot_dict[target_system], 'TG/HDL ratio', 'NR0B2', 'SLCO1B1')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3806ded-dc81-4bce-a9cd-17063bf63660",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Print out epistasis analysis from LLM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "11a0262d-f111-4b0b-b98c-4398ab56d8f6",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from IPython.display import Markdown as md"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "1bedf6b8-29e8-4d8f-9f33-b6f4848287c8",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "### **Analysis of Epistatic Interaction Between NR0B2 and SLCO1B1 in Bile Acid and Bile Salt Transport**\n",
       "\n",
       "#### **1. Biological Roles of NR0B2 and SLCO1B1 in Bile Acid and Bile Salt Transport**\n",
       "\n",
       "- **NR0B2 (Nuclear Receptor Subfamily 0 Group B Member 2, also known as SHP)**  \n",
       "  NR0B2 is an orphan nuclear receptor that functions as a transcriptional repressor. It plays a critical role in bile acid homeostasis by inhibiting the transcriptional activity of other nuclear receptors, such as **FXR (Farnesoid X Receptor)**, which regulates genes involved in bile acid synthesis, transport, and metabolism. Through this repression, NR0B2 helps regulate bile salt production and prevents excessive bile acid accumulation that could be toxic to cells.\n",
       "\n",
       "- **SLCO1B1 (Solute Carrier Organic Anion Transporter Family Member 1B1, also known as OATP1B1)**  \n",
       "  SLCO1B1 is a membrane transporter primarily expressed in hepatocytes. It facilitates the hepatic uptake of bile acids, bile salts, and various endogenous and exogenous organic anions, including statins. By mediating the clearance of bile acids from circulation, SLCO1B1 plays an essential role in maintaining bile acid homeostasis and preventing systemic toxicity.\n",
       "\n",
       "#### **2. Interaction and Influence on the TG/HDL Ratio Phenotype**\n",
       "\n",
       "The **TG/HDL ratio (triglyceride-to-high-density lipoprotein cholesterol ratio)** is an important biomarker for metabolic health, lipid metabolism, and cardiovascular disease risk. \n",
       "\n",
       "- **NR0B2 and Lipid Metabolism:**  \n",
       "  NR0B2 indirectly influences the TG/HDL ratio by regulating bile acid levels, which in turn affect lipid digestion and cholesterol metabolism. It suppresses genes involved in bile acid synthesis, thereby influencing lipid absorption and transport.\n",
       "\n",
       "- **SLCO1B1 and Lipid Metabolism:**  \n",
       "  SLCO1B1 facilitates the hepatic uptake of bile acids, which are important for emulsifying dietary fats and regulating lipid metabolism. Variants in **SLCO1B1** have been associated with altered lipid profiles, affecting the TG/HDL ratio.\n",
       "\n",
       "- **Potential Interaction Impact:**  \n",
       "  If NR0B2 is dysfunctional, bile acid synthesis may increase, potentially altering lipid absorption and leading to dysregulated triglyceride (TG) and HDL levels. If **SLCO1B1 is impaired**, bile acid clearance from circulation may be reduced, further disrupting lipid metabolism. Together, their interaction could exacerbate dyslipidemia, influencing the **TG/HDL ratio** by increasing TG levels and lowering HDL.\n",
       "\n",
       "#### **3. Possible Epistatic Relationships**\n",
       "\n",
       "- **Suppression (Epistasis by Compensation):**  \n",
       "  If NR0B2 is dysfunctional, leading to excessive bile acid synthesis, increased SLCO1B1 activity might compensate by enhancing bile acid clearance, partially mitigating lipid dysregulation. Conversely, if **SLCO1B1 is impaired**, NR0B2-mediated suppression of bile acid synthesis might help prevent excessive bile acid accumulation.\n",
       "\n",
       "- **Redundancy (Buffering Epistasis):**  \n",
       "  If both genes contribute to bile acid regulation independently, loss of one gene might not lead to severe phenotypic effects unless the other is also lost. This would indicate functional redundancy in bile acid transport and metabolism.\n",
       "\n",
       "- **Synthetic Lethality (Severe Dysfunction When Both Are Mutated):**  \n",
       "  If both NR0B2 and SLCO1B1 are disrupted, bile acid homeostasis could collapse, leading to severe metabolic dysfunction, toxic bile acid accumulation, and increased cardiovascular risk due to extreme dyslipidemia.\n",
       "\n",
       "#### **4. Predicted Phenotypic Effects of Gene Perturbations**\n",
       "\n",
       "| **Perturbation** | **Predicted Effect on Bile Acid Transport** | **Predicted Effect on TG/HDL Ratio** |\n",
       "|-----------------|---------------------------------|--------------------------|\n",
       "| **NR0B2 Loss** | Increased bile acid synthesis | Increased TG, decreased HDL |\n",
       "| **SLCO1B1 Loss** | Impaired hepatic bile acid uptake | Increased TG, decreased HDL |\n",
       "| **NR0B2 & SLCO1B1 Loss (Double Mutation)** | Severe bile acid dysregulation | Exacerbated dyslipidemia, extreme TG/HDL imbalance, increased cardiovascular risk |\n",
       "\n",
       "#### **Conclusion**\n",
       "NR0B2 and SLCO1B1 interact in bile acid homeostasis, contributing to lipid metabolism regulation. Their relationship may exhibit **suppressive or buffering epistasis**, where the loss of one gene could be partially compensated by the other. However, **double-gene loss may lead to severe metabolic dysfunction**. Understanding their interaction is crucial for assessing metabolic disease risks and therapeutic interventions, particularly in lipid disorders and cardiovascular health."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md(llm_result)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c3a2e41-902e-4a33-a853-569d2d81a133",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "**You can also visualize llm analysis as diagram!**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "29dcc20e-ea15-41e2-8e1f-3f9adb5e169d",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
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       "<AGraph b'Epistasis' <Swig Object of type 'Agraph_t *' at 0x155450226240>>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "epistasis_explainer.visualize_epistasis_from_llm_analysis(llm_result)"
   ]
  },
  {
   "cell_type": "code",
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