Genotypify

Genotyping lots of samples with big pangenomes

Variables

DIR_BASE=/lizardfs/guarracino/genotypify

Installation on UTHSC cluster

cosigt

Install go:

cd /lizardfs/guarracino/tools
wget -c https://go.dev/dl/go1.23.1.linux-amd64.tar.gz
tar -C /lizardfs/guarracino/tools -xzf go1.23.1.linux-amd64.tar.gz && rm go1.23.1.linux-amd64.tar.gz
#Add 'export PATH="/lizardfs/guarracino/tools/go/bin:$PATH"' to ~/.zshrc

Build cosigt:

cd /lizardfs/guarracino/git
git clone https://github.com/davidebolo1993/cosigt
cd cosigt
go mod init cosigt && go mod tidy && go build cosigt
#Add 'export PATH="/lizardfs/guarracino/git/cosigt:$PATH"' to ~/.zshrc

Create a conda environment for cosigt with all its dependencies:

conda create --prefix /lizardfs/guarracino/condatools/cosigt -c conda-forge -c bioconda -c anaconda -c vikky34v snakemake=7.32.4 cookiecutter=2.6.0 bwa-mem2=2.2.1 megadepth samtools=1.21 bedtools=2.31.1 python=3.9 pyyaml=6.0.2 pandas -y #r-base r-rjson=0.2.23 r-reshape2=1.4.4 r-nbclust=3.0.1 r-data.table r-ggplot2=3.5.1 r-dendextend=1.18.1 r-gggenes=0.5.1 bioconductor-rtracklayer time -y

It assumes that all pggb and its tools (wfmash, seqwish, smoothxg, odgi, gfaffix), samtools, bedtools are in $PATH are installed and included in system's $PATH environment variable so they can be executed from any directory.

MONI

I've added moni on bioconda, so we can just:

conda create --prefix /lizardfs/guarracino/condatools/moni/0.2.2 -c conda-forge -c bioconda moni=0.2.2 -y

Small test

Preparation:

mkdir -p /scratch/small_test && cd /scratch/small_test

# Region-of-interest
mkdir roi && echo -e "grch38#chr6\t31972057\t32055418" > roi/roi.bed

# Cram
mkdir cram && cd cram
wget https://1000genomes.s3.amazonaws.com/1000G_2504_high_coverage/additional_698_related/data/ERR3988768/HG00438.final.cram
wget https://1000genomes.s3.amazonaws.com/1000G_2504_high_coverage/additional_698_related/data/ERR3988768/HG00438.final.cram.crai
cd ..

# Reference
mkdir reference && cd reference
wget ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/technical/reference/GRCh38_reference_genome/GRCh38_full_analysis_set_plus_decoy_hla.fa
samtools faidx GRCh38_full_analysis_set_plus_decoy_hla.fa
cd ..

# Assemblies
curl -L https://github.com/refresh-bio/agc/releases/download/v1.1/agc-1.1_x64-linux.tar.gz | tar -zxvf - agc-1.1_x64-linux/agc
mkdir assemblies && cd assemblies
wget -O HPRC-yr1.agc "https://zenodo.org/record/5826274/files/HPRC-yr1.agc?download=1"
rm chr6.y1.fa
while read -r line; do
    ../agc-1.1_x64-linux/agc getctg HPRC-yr1.agc $line >> chr6.y1.fa
done < $DIR_BASE/data/chr6.y1.txt
samtools faidx ../reference/GRCh38_full_analysis_set_plus_decoy_hla.fa chr6 | sed 's/^>chr6/>grch38#chr6/' > chr6.grhch38.fa
cat chr6.grhch38.fa >> chr6.y1.fa
samtools faidx chr6.y1.fa
cd ..

# Paf
mkdir paf && cd paf
wfmash ../assemblies/chr6.grhch38.fa ../assemblies/chr6.y1.fa -X -t 16 -s 10k -p 95 > chr6.y1.s10p95.paf
cd ..

Genotyping:

export PATH=$(echo $PATH | tr ':' '\n' | awk '!(/\/gnu\/store\// || /guix/)' | paste -sd ':') # Remove guix's path
export PYTHONNOUSERSITE=1 # Tells Python not to use the user site-packages directory and clear the Python path
export PATH="/home/guarracino/.guix-profile/bin:$PATH"
export PATH="/scratch/cosigt:$PATH"

# Activate conda environment
conda activate /lizardfs/guarracino/condatools/cosigt

# Prepare input files
cd /scratch/cosigt/cosigt_smk
python workflow/scripts/organize.py -a /scratch/small_test/cram -r /scratch/small_test/reference/GRCh38_full_analysis_set_plus_decoy_hla.fa --assemblies /scratch/small_test/assemblies/chr6.y1.fa --roi /scratch/small_test/roi/roi.bed --pggb_tmpdir /scratch

# Genotyping
snakemake cosigt --cores 16

conda deactivate

Data

Ancient

15 samples from Marchi et al., 2022 (https://doi.org/10.1016/j.cell.2022.04.008).

mkdir -p $DIR_BASE/sequencing_data/ancient

# Download the submitted FASTQ files, discarding the XXX_realg.noclips_splitRG.bam files
mkdir -p /scratch/Marchi2022
cd /scratch/Marchi2022
grep -Ff <(sed '1d' $DIR_BASE/data/Marchi2022.TableS1.csv | cut -f 9 | sed 's/SL_MU_/SLMU/g') $DIR_BASE/data/filereport_read_run_PRJEB50857_tsv.txt | awk -F'\t' 'NR>1 {split($8, a, ";"); for (i in a) print "ftp://"a[i]}' | xargs -n 1 wget

cd /scratch
mv /scratch/Marchi2022 $DIR_BASE/sequencing_data/ancient

# Marchi2022.TableS1.csv to map `SAMPLE <-> FILE`

315 (317 - 2 samples with missing FASTQ files) samples from Allentoft et al., 2024 (https://doi.org/10.1038/s41586-023-06865-0):

# Counts of ancient samples they collected from other studies
sed '1d' Allentoft2024.SupplementaryData7.csv | cut -f 8 | sort | uniq -c | sort -k 1,1n

mkdir -p $DIR_BASE/sequencing_data/ancient/Allentoft2024
cd /scratch
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB64656_tsv.txt | cut -f 7 | grep ftp | awk -F'\t' 'NR>1 {split($1, a, ";"); for (i in a) print "ftp://"a[i]}' | xargs -n 1 -I {} sh -c 'wget {}; mv $(basename {}) /lizardfs/guarracino/genotypify/sequencing_data/ancient/Allentoft2024'

# To map `SAMPLE <-> FILE`
(sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB64656_tsv.txt | cut -f 7,8 | grep 'NEO898\|NEO813\|ERR12075080' -v | awk -v FS='/' '{print($7,$12)}' | sed -e 's/ftp.sra.ebi.ac.uk//g' -e 's/.fastq.gz//g' -e 's/.sort.rmdup.realign.md.bam;//g' -e 's/.neo.merge.bam;//g' -e 's/.neo.clean.bam;//g' | sed 's/ //g'; echo "ERR12075080\tNEO962")

442 samples from Margaryan et al., 2020 (https://doi.org/10.1038/s41586-020-2688-8; https://www.ebi.ac.uk/ena/browser/view/PRJEB37976):

mkdir -p $DIR_BASE/sequencing_data/ancient/Margaryan2020
cd /scratch/
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB37976_tsv.txt | cut -f 7 | xargs -n 1 -I {} sh -c 'wget {}; mv $(basename {}) /lizardfs/guarracino/genotypify/sequencing_data/ancient/Margaryan2020'

# To map `SAMPLE <-> FILE`
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB37976_tsv.txt | cut -f 7,8 | awk -v FS='/' '{print($7,$12)}' | sed -e 's/ftp.sra.ebi.ac.uk//g' -e 's/.fastq.gz//g' -e 's/.final.bam//g' | sed 's/ //g'

134 samples from Antonio et al., 2019 (https://www.ebi.ac.uk/ena/browser/view/PRJEB32566; https://www.ebi.ac.uk/ena/browser/view/PRJEB32566):

mkdir -p $DIR_BASE/sequencing_data/ancient/Antonio2019
cd /scratch/
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB32566_tsv.txt | cut -f 7 | xargs -n 1 -I {} sh -c 'wget {}; mv $(basename {}) /lizardfs/guarracino/genotypify/sequencing_data/ancient/Antonio2019'

# To map `SAMPLE <-> FILE`
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB32566_tsv.txt | cut -f 7,8 | awk -v FS='/' '{print($7,$12)}' | sed -e 's/ftp.sra.ebi.ac.uk//g' -e 's/.fastq.gz//g' -e 's/.bam;//g' -e 's/.bam//g' | sed 's/ //g'

137 samples from Damgaard et al., 2018, Nature (https://doi.org/10.1038/s41586-018-0094-2; https://www.ebi.ac.uk/ena/browser/view/PRJEB20658):

mkdir -p $DIR_BASE/sequencing_data/ancient/Damgaard2018_Nature
cd /scratch
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB20658_tsv.txt | cut -f 7 | xargs -n 1 -I {} sh -c 'wget {}; mv $(basename {}) /lizardfs/guarracino/genotypify/sequencing_data/ancient/Damgaard2018_Nature'

# To map `SAMPLE <-> FILE`
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB20658_tsv.txt | cut -f 7,8 | awk -v FS='/' '{print($7,$12)}' | sed -e 's/ftp.sra.ebi.ac.uk//g' -e 's/.fastq.gz//g' -e 's/.sort.rmdup.realign.md.bam;//g' | sed 's/ //g'

70 samples from Damgaard et al., 2018, Science (https://doi.org/10.1126/science.aar7711; https://www.ebi.ac.uk/ena/browser/view/PRJEB25389 and https://www.ebi.ac.uk/ena/browser/view/PRJEB26349):

# 70 samples, but the paper mentions 74 samples
mkdir -p $DIR_BASE/sequencing_data/ancient/Damgaard2018_Science
cd /scratch
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB26349_tsv.txt | grep -Ff <(sed '1d' $DIR_BASE/data/Damgaard2018.Science.SupplementaryTable1.csv | cut -f 1) | cut -f 7 | xargs -n 1 -I {} sh -c 'wget {}; mv $(basename {}) /lizardfs/guarracino/genotypify/sequencing_data/ancient/Damgaard2018_Science'

# The 4 missed samples are in the Damgaard et al., 2018, Nature paper
sed '1d' $DIR_BASE/data/Damgaard2018.Science.SupplementaryTable1.csv | cut -f 1 | sort | grep -Ff <(sed '1d' data/filereport_read_run_PRJEB26349_tsv.txt | grep -Ff <(sed '1d' data/Damgaard2018.Science.SupplementaryTable1.csv | cut -f 1) | cut -f 8 | cut -f 6 -d '/' | cut -f 1 -d '.' | cut -f 1 -d '_' ) -v
# DA343
# DA353
# DA356
# DA361

102 samples from Allentoft et al., 2015 (https://doi.org/10.1038/nature14507; https://www.ebi.ac.uk/ena/browser/view/PRJEB9021).

mkdir -p $DIR_BASE/sequencing_data/ancient/Allentoft2015
cd /scratch
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB9021_tsv.txt | cut -f 7 | xargs -n 1 -I {} sh -c 'wget {}; mv $(basename {}) /lizardfs/guarracino/genotypify/sequencing_data/ancient/Allentoft2015'

# To map `SAMPLE <-> FILE`
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB9021_tsv.txt | cut -f 7,8 | awk -v FS='/' '{print($6,$11)}' | sed -e 's/ftp.sra.ebi.ac.uk//g' -e 's/.fastq.gz//g' | sed -e 's/.hg19.flt.sort.rmdup.realign.md.bam//g' | sed 's/ //g'

58 samples from Brunel et al., 2020 (https://doi.org/10.1073/pnas.1918034117; https://www.ebi.ac.uk/ena/browser/view/PRJEB38152)

#sed '1d' filereport_read_run_PRJEB38152_tsv.txt | grep -i -Ff <(sed '1,2d' Brunel2018.SupplementaryTable1.csv | cut -f 1 | sed -e 's/Schw72-15/Sch72-15/g' -e 's/CRE8C/CRE8-C/g' -e 's/BIS388-/BIS388/g'; echo CRE20D)
mkdir -p $DIR_BASE/sequencing_data/ancient/Brunel2020
cd /scratch
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB38152_tsv.txt | grep bam | cut -f 7 | xargs -n 1 -I {} sh -c 'wget {}; mv $(basename {}) /lizardfs/guarracino/genotypify/sequencing_data/ancient/Brunel2020'

# To map `SAMPLE <-> FILE`
sed '1d' filereport_read_run_PRJEB38152_tsv.txt | cut -f 7,8 | grep bam | awk -v FS='/' '{print($7,$12)}' | sed -e 's/ftp.sra.ebi.ac.uk//g' -e 's/.fastq.gz//g' | sed -e 's/.mappedHs37d5.trim2.bam//g' -e 's/.mappedHs37d5.trim2.bam//g' -e 's/.mappedHs37.trim2.bam//g' | sed 's/ //g'

91??? samples frm Scheib et al., 2018 (https://doi.org/10.1126/science.aar6851; https://www.ebi.ac.uk/ena/browser/view/PRJEB25445)

mkdir -p $DIR_BASE/sequencing_data/ancient/Scheib2018
cd /scratch
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB25445_tsv.txt | cut -f 7 | grep ftp | xargs -n 1 -I {} sh -c 'wget {}; mv $(basename {}) /lizardfs/guarracino/genotypify/sequencing_data/ancient/Scheib2018'

# Check Scheib2018.SupplementaryTable1.tsv and Scheib2018.SupplementaryTable3.tsv (number of reads) to process downloaded samples

34 samples from Sikora et al.m 2019 (https://doi.org/10.1038/s41586-019-1279-z; https://www.ebi.ac.uk/ena/browser/view/PRJEB29700 and https://www.ebi.ac.uk/ena/browser/view/PRJEB26336):

mkdir -p $DIR_BASE/sequencing_data/ancient/Sikora2019
cd /scratch
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB29700_tsv.txt | cut -f 7 | xargs -n 1 -I {} sh -c 'wget {}; mv $(basename {}) /lizardfs/guarracino/genotypify/sequencing_data/ancient/Sikora2019'

# To map `SAMPLE <-> FILE`
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB29700_tsv.txt | cut -f 7,8 | awk -v FS='/' '{print($7,$12)}' | sed -e 's/ftp.sra.ebi.ac.uk//g' -e 's/.fastq.gz//g' -e 's/.sort.rmdup.realign.md.bam;//g' -e 's/.realigned.calmd.readsadded.bam;//g' -e 's/.sort.rmdup.uniq.rg.realn.md.bam;//g' | sed 's/ //g'

35 samples from Krzewinska et al., 2018 (https://doi.org/10.1126/sciadv.aat4457; https://www.ebi.ac.uk/ena/browser/view/PRJEB27628):

mkdir -p $DIR_BASE/sequencing_data/ancient/Krzewinska2018
cd /scratch
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB27628_tsv.txt | cut -f 7 | xargs -n 1 -I {} sh -c 'wget {}; mv $(basename {}) /lizardfs/guarracino/genotypify/sequencing_data/ancient/Krzewinska2018'

# To map `SAMPLE <-> FILE`
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB27628_tsv.txt | cut -f 7,8 | awk -v FS='/' '{print($7,$12)}' | sed -e 's/ftp.sra.ebi.ac.uk//g' -e 's/.fastq.gz//g' | cut -f 1 -d '_' | sed 's/ //g'

25 samples from McColl et al., 2018 (https://doi.org/10.1126/science.aat3628; https://www.ebi.ac.uk/ena/browser/view/PRJEB26721)

mkdir -p $DIR_BASE/sequencing_data/ancient/McColl2018
cd /scratch
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB26721_tsv.txt | cut -f 7 | awk -F'\t' 'NR>1 {split($1, a, ";"); for (i in a) print "ftp://"a[i]}' | xargs -n 1 -I {} sh -c 'wget {}; mv $(basename {}) /lizardfs/guarracino/genotypify/sequencing_data/ancient/McColl2018'

Ebenesersdottir et al.m 2018, Science (https://doi.org/10.1126/science.aar2625): I NEED ACCESS TO THE PUBLICATION

15/24?? samples from Schroeder et al., 2019 (https://doi.org/10.1073/pnas.1820210116; https://www.ebi.ac.uk/ena/browser/view/PRJEB28451):

mkdir -p $DIR_BASE/sequencing_data/ancient/Schroeder2019
cd /scratch
sed '1d' $DIR_BASE/data/filereport_read_run_PRJEB28451_tsv.txt | cut -f 7 | xargs -n 1 -I {} sh -c 'wget {}; mv $(basename {}) /lizardfs/guarracino/genotypify/sequencing_data/ancient/Schroeder2019'

Modern

1000 Genomes Project sample collection to 30x coverage (from https://www.internationalgenome.org/data-portal/data-collection/30x-grch38). Initially, the 2504 unrelated samples from the phase three panel from the 1000 Genomes Project were sequenced. Thereafter, an additional 698 samples, related to samples in the 2504 panel, were also sequenced.

mkdir -p $DIR_BASE/sequencing_data/modern/1000G/2504_high_coverage
cd $DIR_BASE/sequencing_data/modern/1000G/2504_high_coverage
wget -c https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000G_2504_high_coverage/1000G_2504_high_coverage.sequence.index
awk '!/^#/ {print $1}' 1000G_2504_high_coverage.sequence.index | xargs -n 1 wget

mkdir -p $DIR_BASE/sequencing_data/modern/1000G/additional_698_related
cd $DIR_BASE/sequencing_data/modern/1000G/additional_698_related
wget -c http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000G_2504_high_coverage/1000G_698_related_high_coverage.sequence.index
awk '!/^#/ {print $1}' 1000G_698_related_high_coverage.sequence.index | xargs -n 1 wget

Simons Genome Diversity Project (from https://www.ebi.ac.uk/ena/browser/view/PRJEB9586):

mkdir -p $DIR_BASE/sequencing_data/modern/SGDP/
cd $DIR_BASE/sequencing_data/modern/SGDP/
wget -c https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/HGDP/hgdp_wgs.sequence.index
awk -F'\t' 'NR>1 {split($7, a, ";"); for (i in a) print "ftp://"a[i]}' $DIR_BASE/data/filereport_read_run_PRJEB9586_tsv.txt | xargs -n 1 wget

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Genotypify

Variables

Installation on UTHSC cluster

cosigt

MONI

Small test

Data

Ancient

Modern

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Genotypify

Variables

Installation on UTHSC cluster

cosigt

MONI

Small test

Data

Ancient

Modern

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