diff --git a/_sources/code/data_preprocessing/genotype/GWAS_QC.ipynb b/_sources/code/data_preprocessing/genotype/GWAS_QC.ipynb index e079cdd22..badba01b0 100644 --- a/_sources/code/data_preprocessing/genotype/GWAS_QC.ipynb +++ b/_sources/code/data_preprocessing/genotype/GWAS_QC.ipynb @@ -1,22 +1,20 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", - "id": "gross-treaty", + "id": "framed-fishing", "metadata": { "kernel": "SoS" }, "source": [ "# Genotype PLINK file quality control\n", "\n", - "This workflow implements some prelimary data QC steps for PLINK input files. VCF format of inputs will be converted to PLINK before performing QC." + "This workflow implements some preliminary data QC steps for PLINK input files. VCF format of inputs will be converted to PLINK before performing QC." ] }, { - "attachments": {}, "cell_type": "markdown", - "id": "tamil-forestry", + "id": "demographic-return", "metadata": { "kernel": "SoS" }, @@ -44,9 +42,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", - "id": "bound-watson", + "id": "roman-variety", "metadata": { "kernel": "SoS" }, @@ -54,22 +51,22 @@ "## Default QC parameters\n", "\n", "- Kinship coefficient for related individuals: 0.0625\n", - "- MAF default: 0\n", + "- MAF and MAC default: 0\n", " - Above default includes both common and are variant\n", " - Recommand MAF for PCA: 0.01, [we should stick to common variants](https://bmcgenomdata.biomedcentral.com/articles/10.1186/s12863-020-0833-x)\n", - " - Recommand MAC for single variant analysis: 5\n", + " - Recommand MAC for single variant analysis: 5.\n", "- Variant level missingness threshold: 0.1\n", "- Sample level missingness threshold: 0.1\n", "- LD pruning via PLINK for PCA analysis:\n", " - window 50 \n", " - shift 10 \n", - " - r2 0.1" + " - r2 0.1\n", + "- HWE default: 1E-15 which is very lenient" ] }, { - "attachments": {}, "cell_type": "markdown", - "id": "brutal-tower", + "id": "raising-civilian", "metadata": { "kernel": "SoS", "tags": [] @@ -77,18 +74,17 @@ "source": [ "## Minimal working example\n", "\n", - "Minimal working example data-set as well as the singularity container `bioinfo.sif` can be downloaded from [Google Drive](https://drive.google.com/drive/u/0/folders/1ahIZGnmjcGwSd-BI91C9ayd_Ya8sB2ed).\n", + "Minimal working example data-set as well as the singularity container `bioinfo.sif` can be downloaded from [Google Drive](https://drive.google.com/drive/u/0/folders/1ahIZGnmjcGwSd-BI91C9ayd_Ya8sB2ed). FIXME: use synapse link\n", "\n", "The `chr1_chr6` data-set was merged from `chr1` and `chr6` data, using `merge_plink` command from [genotype formatting](https://cumc.github.io/xqtl-pipeline/code/data_preprocessing/genotype/genotype_formatting.html) pipeline.\n", "\n", - "\n", "### Example 1: perform QC on both rare and common variants" ] }, { "cell_type": "code", "execution_count": null, - "id": "southern-glasgow", + "id": "ranking-kidney", "metadata": { "jp-MarkdownHeadingCollapsed": true, "kernel": "Bash", @@ -103,9 +99,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", - "id": "traditional-grounds", + "id": "several-exemption", "metadata": { "kernel": "SoS", "tags": [] @@ -119,7 +114,7 @@ { "cell_type": "code", "execution_count": null, - "id": "integrated-prompt", + "id": "changing-lesson", "metadata": { "jp-MarkdownHeadingCollapsed": true, "kernel": "Bash", @@ -137,7 +132,7 @@ { "cell_type": "code", "execution_count": null, - "id": "840744dd-3369-477b-8a7f-108dfc3d5902", + "id": "developed-leeds", "metadata": {}, "outputs": [], "source": [ @@ -149,9 +144,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", - "id": "awful-camping", + "id": "thermal-thread", "metadata": { "jp-MarkdownHeadingCollapsed": true, "kernel": "SoS", @@ -164,7 +158,7 @@ { "cell_type": "code", "execution_count": null, - "id": "incorrect-probability", + "id": "happy-works", "metadata": { "kernel": "Bash" }, @@ -179,9 +173,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", - "id": "enhanced-commissioner", + "id": "whole-display", "metadata": { "kernel": "Bash" }, @@ -192,7 +185,7 @@ { "cell_type": "code", "execution_count": null, - "id": "palestinian-scoop", + "id": "considerable-belize", "metadata": { "kernel": "Bash" }, @@ -208,9 +201,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", - "id": "dental-annex", + "id": "threatened-package", "metadata": { "kernel": "Bash", "tags": [] @@ -222,7 +214,7 @@ { "cell_type": "code", "execution_count": 1, - "id": "supposed-memorabilia", + "id": "disturbed-airfare", "metadata": { "kernel": "Bash" }, @@ -341,7 +333,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fluid-subsection", + "id": "productive-doctrine", "metadata": { "kernel": "SoS" }, @@ -375,17 +367,15 @@ "parameter: numThreads = 20\n", "# Software container option\n", "parameter: container = \"\"\n", - "if not container:\n", - " container = None\n", + "parameter: entrypoint={('micromamba run -n' + ' ' + container.split('/')[-1][:-4]) if container.endswith('.sif') else f''}\n", "# use this function to edit memory string for PLINK input\n", "from sos.utils import expand_size\n", "cwd = path(f\"{cwd:a}\")" ] }, { - "attachments": {}, "cell_type": "markdown", - "id": "south-hardware", + "id": "formed-baseline", "metadata": { "kernel": "SoS" }, @@ -398,7 +388,7 @@ { "cell_type": "code", "execution_count": null, - "id": "occasional-production", + "id": "married-withdrawal", "metadata": { "kernel": "SoS" }, @@ -411,7 +401,7 @@ "input: genoFile\n", "output: f'{cwd}/{_input:bn}{(\".\"+name) if name else \"\"}.kin0'\n", "task: trunk_workers = 1, trunk_size = job_size, walltime = walltime, mem = mem, cores = numThreads, tags = f'{step_name}_{_output:bn}'\n", - "bash: container=container, expand= \"${ }\", stderr = f'{_output}.stderr', stdout = f'{_output}.stdout'\n", + "bash: container=container, expand= \"${ }\", stderr = f'{_output}.stderr', stdout = f'{_output}.stdout', entrypoint=entrypoint\n", " plink2 \\\n", " --bfile ${_input:n} \\\n", " --make-king-table \\\n", @@ -424,21 +414,20 @@ " --threads ${numThreads} \\\n", " --memory ${int(expand_size(mem) * 0.9)/1e6} \n", " \n", - "bash: expand= \"$[ ]\", stderr = f'{_output:n}.stderr', stdout = f'{_output}.stdout', container = container\n", - " stdout=$[_output].stdout\n", - " for i in $[_output] ; do \n", - " echo \"output_info: $i \" >> $stdout;\n", - " echo \"output_size:\" `ls -lh $i | cut -f 5 -d \" \"` >> $stdout;\n", - " echo \"output_rows:\" `zcat $i | wc -l | cut -f 1 -d \" \"` >> $stdout;\n", - " echo \"output_column:\" `zcat $i | head -1 | wc -w ` >> $stdout;\n", - " echo \"output_preview:\" >> $stdout;\n", - " cat $i | grep -v \"##\" | head | cut -f 1,2,3,4,5,6 >> $stdout ; done" + "bash: expand= \"${ }\", stderr = f'{_output:n}.stderr', stdout = f'{_output}.stdout', container = container, entrypoint=entrypoint\n", + " i=\"${_output}\"\n", + " output_size=$(ls -lh $i | cut -f 5 -d ' ')\n", + " output_rows=$(zcat $i | wc -l | cut -f 1 -d ' ')\n", + " output_column=$(zcat $i | head -1 | wc -w)\n", + " output_preview=$(cat $i | grep -v \"##\" | head | cut -f 1,2,3,4,5,6)\n", + " \n", + " printf \"output_info: %s\\noutput_size: %s\\noutput_rows: %s\\noutput_column: %s\\noutput_preview:\\n%s\\n\" \\\n", + " \"$i\" \"$output_size\" \"$output_rows\" \"$output_column\" \"$output_preview\" >> ${_output}.stdout" ] }, { - "attachments": {}, "cell_type": "markdown", - "id": "44e38a12-53ef-4662-b6be-1c89cc21edee", + "id": "prompt-advocate", "metadata": { "kernel": "SoS" }, @@ -447,7 +436,7 @@ { "cell_type": "code", "execution_count": null, - "id": "brilliant-hours", + "id": "cathedral-tension", "metadata": { "kernel": "SoS" }, @@ -461,7 +450,7 @@ "parameter: maximize_unrelated = False\n", "output: f'{_input:n}.related_id'\n", "task: trunk_workers = 1, trunk_size = job_size, walltime = walltime, mem = mem, cores = numThreads, tags = f'{step_name}_{_output:bn}'\n", - "R: container=container, expand= \"${ }\", stderr = f'{_output}.stderr', stdout = f'{_output}.stdout'\n", + "R: container=container, expand= \"${ }\", stderr = f'{_output}.stderr', stdout = f'{_output}.stdout', entrypoint=entrypoint\n", " library(dplyr)\n", " library(igraph)\n", " # Remove related individuals while keeping maximum number of individuals\n", @@ -646,21 +635,21 @@ " cat(\"There are\", nrow(dat),\"related individuals using a kinship threshold of ${kinship}\\n\")\n", " write.table(dat,${_output:r}, quote=FALSE, row.names=FALSE, col.names=FALSE)\n", " \n", - "bash: expand= \"$[ ]\", stderr = f'{_output}.stderr', stdout = f'{_output}.stdout', container = container\n", - " stdout=$[_output].stdout\n", - " for i in $[_output] ; do \n", - " echo \"output_info: $i \" >> $stdout;\n", - " echo \"output_size:\" `ls -lh $i | cut -f 5 -d \" \"` >> $stdout;\n", - " echo \"output_rows:\" `zcat $i | wc -l | cut -f 1 -d \" \"` >> $stdout;\n", - " echo \"output_column:\" `zcat $i | head -1 | wc -w ` >> $stdout;\n", - " echo \"output_preview:\" >> $stdout;\n", - " cat $i | grep -v \"##\" | head | cut -f 1,2,3,4,5,6 >> $stdout ; done" + "bash: expand= \"${ }\", stderr = f'{_output:n}.stderr', stdout = f'{_output}.stdout', container = container, entrypoint=entrypoint\n", + " i=\"${_output}\"\n", + " output_size=$(ls -lh $i | cut -f 5 -d ' ')\n", + " output_rows=$(zcat $i | wc -l | cut -f 1 -d ' ')\n", + " output_column=$(zcat $i | head -1 | wc -w)\n", + " output_preview=$(cat $i | grep -v \"##\" | head | cut -f 1,2,3,4,5,6)\n", + " \n", + " printf \"output_info: %s\\noutput_size: %s\\noutput_rows: %s\\noutput_column: %s\\noutput_preview:\\n%s\\n\" \\\n", + " \"$i\" \"$output_size\" \"$output_rows\" \"$output_column\" \"$output_preview\" >> ${_output}.stdout" ] }, { "cell_type": "code", "execution_count": null, - "id": "infrared-butter", + "id": "thick-horse", "metadata": { "kernel": "SoS" }, @@ -674,7 +663,7 @@ "related_id = [x.strip() for x in open(_input[0]).readlines()]\n", "stop_if(len(related_id) == 0)\n", "task: trunk_workers = 1, trunk_size = job_size, walltime = walltime, mem = mem, cores = numThreads, tags = f'{step_name}_{_output[0]:bn}'\n", - "bash: expand= \"${ }\", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', container = container\n", + "bash: expand= \"${ }\", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', container = container, entrypoint=entrypoint\n", " plink2 \\\n", " --bfile ${_input[1]:n} \\\n", " --remove ${_input[0]} \\\n", @@ -692,18 +681,16 @@ " --threads ${numThreads} \\\n", " --memory ${int(expand_size(mem) * 0.9)/1e6} --new-id-max-allele-len 1000 --set-all-var-ids chr@:#_\\$r_\\$a \n", " \n", - "bash: expand= \"$[ ]\", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', container = container\n", - " stdout=$[_output[0]:n].stdout\n", - " for i in $[_output] ; do \n", - " echo \"output_info: $i \" >> $stdout;\n", - " echo \"output_size:\" `ls -lh $i | cut -f 5 -d \" \"` >> $stdout;\n", - " done" + "bash: expand= \"${ }\", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', container = container, entrypoint=entrypoint\n", + " for i in ${_output}; do \n", + " output_size=$(ls -lh $i | cut -f 5 -d ' ')\n", + " printf \"output_info: %s\\noutput_size: %s\\n\" \"$i\" \"$output_size\" >> ${_output[0]:n}.stdout\n", + " done" ] }, { - "attachments": {}, "cell_type": "markdown", - "id": "standing-spencer", + "id": "honest-variable", "metadata": { "kernel": "SoS" }, @@ -720,7 +707,7 @@ { "cell_type": "code", "execution_count": 2, - "id": "average-austin", + "id": "active-progress", "metadata": { "kernel": "SoS" }, @@ -756,7 +743,7 @@ "input: genoFile, group_by=1\n", "output: f'{cwd}/{_input:bn}{(\".\"+name) if name else \"\"}.plink_qc{\".extracted\" if keep_variants.is_file() else \"\"}{\".bed\" if not meta_only else \".snplist\"}'\n", "task: trunk_workers = 1, trunk_size = job_size, walltime = walltime, mem = mem, cores = numThreads, tags = f'{step_name}_{_output:bn}'\n", - "bash: container=container, volumes=[f'{cwd}:{cwd}'], expand= \"${ }\", stderr = f'{_output:n}.stderr', stdout = f'{_output:n}.stdout'\n", + "bash: container=container, volumes=[f'{cwd}:{cwd}'], expand= \"${ }\", stderr = f'{_output:n}.stderr', stdout = f'{_output:n}.stdout', entrypoint=entrypoint\n", " plink2 \\\n", " --bfile ${_input:n} \\\n", " ${('--maf %s' % maf_filter) if maf_filter > 0 else ''} \\\n", @@ -777,18 +764,16 @@ " --threads ${numThreads} \\\n", " --memory ${int(expand_size(mem) * 0.9)/1e6} --new-id-max-allele-len 1000 --set-all-var-ids chr@:#_\\$r_\\$a \n", " \n", - "bash: expand= \"$[ ]\", stderr = f'{_output:n}.stderr', stdout = f'{_output:n}.stdout', container = container\n", - " stdout=$[_output:n].stdout\n", - " for i in $[_output] ; do \n", - " echo \"output_info: $i \" >> $stdout;\n", - " echo \"output_size:\" `ls -lh $i | cut -f 5 -d \" \"` >> $stdout;\n", - " done" + "bash: expand= \"${ }\", stderr = f'{_output:n}.stderr', stdout = f'{_output:n}.stdout', container = container, entrypoint=entrypoint\n", + " i=\"${_output}\"\n", + " output_size=$(ls -lh $i | cut -f 5 -d ' ')\n", + " printf \"output_info: %s\\noutput_size: %s\\n\" \"$i\" \"$output_size\" >> ${_output:n}.stdout" ] }, { "cell_type": "code", "execution_count": 1, - "id": "numerous-literature", + "id": "multiple-defense", "metadata": { "kernel": "SoS" }, @@ -805,7 +790,7 @@ "stop_if(r2==0)\n", "output: bed=f'{cwd}/{_input:bn}.prune.bed', prune=f'{cwd}/{_input:bn}.prune.in'\n", "task: trunk_workers = 1, trunk_size = job_size, walltime = walltime, mem = mem, cores = numThreads, tags = f'{step_name}_{_output[0]:bn}'\n", - "bash: container=container, expand= \"${ }\", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout'\n", + "bash: container=container, expand= \"${ }\", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', entrypoint=entrypoint\n", " plink2 \\\n", " --bfile ${_input:n} \\\n", " --indep-pairwise ${window} ${shift} ${r2} \\\n", @@ -821,25 +806,23 @@ " --threads ${numThreads} \\\n", " --memory ${int(expand_size(mem) * 0.9)/1e6}\n", " \n", - "bash: expand= \"$[ ]\", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', container = container\n", - " stdout=$[_output[0]:n].stdout\n", - " for i in $[_output[0]] ; do \n", - " echo \"output_info: $i \" >> $stdout;\n", - " echo \"output_size:\" `ls -lh $i | cut -f 5 -d \" \"` >> $stdout;\n", - " done\n", - " for i in $[_output[1]] ; do \n", - " echo \"output_info $i \" >> $stdout;\n", - " echo \"output_size:\" `ls -lh $i | cut -f 5 -d \" \"` >> $stdout;\n", - " echo \"output_rows:\" `zcat $i | wc -l | cut -f 1 -d \" \"` >> $stdout;\n", - " echo \"output_column:\" `zcat $i | head -1 | wc -w ` >> $stdout;\n", - " echo \"output_preview:\" >> $stdout;\n", - " zcat $i | head | cut -f 1,2,3,4,5,6 >> $stdout ; done" + "bash: expand= \"${ }\", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', container = container, entrypoint=entrypoint\n", + " i=\"${_output[0]}\"\n", + " output_size=$(ls -lh $i | cut -f 5 -d ' ')\n", + " printf \"output_info: %s\\noutput_size: %s\\n\" \"$i\" \"$output_size\" >> ${_output[0]:n}.stdout\n", + " i=\"${_output[1]}\"\n", + " output_size=$(ls -lh $i | cut -f 5 -d ' ')\n", + " output_rows=$(zcat $i | wc -l | cut -f 1 -d ' ')\n", + " output_column=$(zcat $i | head -1 | wc -w)\n", + " output_preview=$(cat $i | grep -v \"##\" | head | cut -f 1,2,3,4,5,6) \n", + " printf \"output_info: %s\\noutput_size: %s\\noutput_rows: %s\\noutput_column: %s\\noutput_preview:\\n%s\\n\" \\\n", + " \"$i\" \"$output_size\" \"$output_rows\" \"$output_column\" \"$output_preview\" >> ${_output[1]}.stdout" ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -853,7 +836,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.12" + "version": "3.8.5" }, "nbdime-conflicts": { "local_diff": [ diff --git a/_sources/code/data_preprocessing/genotype/VCF_QC.ipynb b/_sources/code/data_preprocessing/genotype/VCF_QC.ipynb index ad3a36ddb..dd08b63eb 100644 --- a/_sources/code/data_preprocessing/genotype/VCF_QC.ipynb +++ b/_sources/code/data_preprocessing/genotype/VCF_QC.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "damaged-trunk", + "id": "scientific-inspiration", "metadata": { "kernel": "SoS", "tags": [] @@ -13,7 +13,7 @@ }, { "cell_type": "markdown", - "id": "handmade-loading", + "id": "northern-primary", "metadata": { "kernel": "SoS" }, @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "detailed-specialist", + "id": "competitive-enemy", "metadata": { "kernel": "SoS" }, @@ -46,7 +46,7 @@ }, { "cell_type": "markdown", - "id": "auburn-formation", + "id": "dress-influence", "metadata": { "kernel": "SoS" }, @@ -69,7 +69,7 @@ }, { "cell_type": "markdown", - "id": "presidential-hello", + "id": "banner-portrait", "metadata": { "kernel": "SoS", "tags": [] @@ -94,7 +94,7 @@ }, { "cell_type": "markdown", - "id": "internal-thomson", + "id": "patient-catering", "metadata": { "kernel": "SoS" }, @@ -112,7 +112,7 @@ }, { "cell_type": "markdown", - "id": "noticed-entry", + "id": "inclusive-reconstruction", "metadata": { "kernel": "SoS" }, @@ -134,7 +134,7 @@ }, { "cell_type": "markdown", - "id": "ignored-journalism", + "id": "wicked-teens", "metadata": { "kernel": "SoS" }, @@ -142,20 +142,20 @@ "The MWE was used as follows:\n", "\n", "```\n", - "sos run pipeline/VCF_QC.ipynb rename_chrs \\\n", + "sos run VCF_QC.ipynb rename_chrs \\\n", " --genoFile reference_data/00-All.vcf.gz \\\n", " --cwd reference_data --container bioinfo.sif\n", "```\n", "\n", "```\n", - "sos run pipeline/VCF_QC.ipynb dbsnp_annotate \\\n", + "sos run VCF_QC.ipynb dbsnp_annotate \\\n", " --genoFile reference_data/00-All.add_chr.vcf.gz \\\n", " --cwd reference_data --container bioinfo.sif\n", "```\n", "\n", "\n", "```\n", - "sos run pipeline/VCF_QC.ipynb qc \\\n", + "sos run VCF_QC.ipynb qc \\\n", " --genoFile data/MWE/MWE_genotype.vcf \\\n", " --dbsnp-variants data/reference_data/00-All.add_chr.variants.gz \\\n", " --reference-genome data/reference_data/GRCh38_full_analysis_set_plus_decoy_hla.noALT_noHLA_noDecoy_ERCC.fasta \\\n", @@ -165,7 +165,7 @@ "To run in parallel for all genotype data listed in `mwe_genotype_list`,\n", "\n", "```\n", - "sos run pipeline/VCF_QC.ipynb qc \\\n", + "sos run VCF_QC.ipynb qc \\\n", " --genoFile data/mwe/mwe_genotype_list \\\n", " --dbsnp-variants data/reference_data/00-All.add_chr.variants.gz \\\n", " --reference-genome data/reference_data/GRCh38_full_analysis_set_plus_decoy_hla.noALT_noHLA_noDecoy_ERCC.fasta \\\n", @@ -177,7 +177,7 @@ }, { "cell_type": "markdown", - "id": "fluid-ivory", + "id": "ranging-kansas", "metadata": { "kernel": "SoS" }, @@ -192,7 +192,7 @@ { "cell_type": "code", "execution_count": 13, - "id": "floppy-aluminum", + "id": "commercial-wagon", "metadata": { "kernel": "SoS" }, @@ -211,7 +211,7 @@ }, { "cell_type": "markdown", - "id": "choice-round", + "id": "otherwise-gnome", "metadata": { "kernel": "SoS" }, @@ -222,7 +222,7 @@ { "cell_type": "code", "execution_count": 4, - "id": "finite-gauge", + "id": "tribal-product", "metadata": { "kernel": "SoS" }, @@ -241,7 +241,7 @@ }, { "cell_type": "markdown", - "id": "conventional-communications", + "id": "wrapped-indie", "metadata": { "kernel": "SoS" }, @@ -252,7 +252,7 @@ { "cell_type": "code", "execution_count": null, - "id": "chronic-scholar", + "id": "thorough-microwave", "metadata": { "kernel": "SoS" }, @@ -264,7 +264,7 @@ }, { "cell_type": "markdown", - "id": "frozen-commercial", + "id": "approximate-patient", "metadata": { "kernel": "SoS" }, @@ -275,7 +275,7 @@ { "cell_type": "code", "execution_count": 1, - "id": "digital-member", + "id": "coupled-pipeline", "metadata": { "kernel": "Bash", "tags": [] @@ -372,7 +372,7 @@ }, { "cell_type": "markdown", - "id": "statistical-berkeley", + "id": "square-smoke", "metadata": { "kernel": "Bash" }, @@ -383,7 +383,7 @@ { "cell_type": "code", "execution_count": null, - "id": "meaningful-marketplace", + "id": "thrown-wheat", "metadata": { "kernel": "SoS" }, @@ -463,7 +463,7 @@ }, { "cell_type": "markdown", - "id": "psychological-correction", + "id": "paperback-requirement", "metadata": { "kernel": "SoS", "tags": [] @@ -479,7 +479,7 @@ { "cell_type": "code", "execution_count": null, - "id": "electrical-breeding", + "id": "brown-national", "metadata": { "kernel": "SoS" }, @@ -487,7 +487,7 @@ "source": [ "[rename_chrs: provides = '{filename}.add_chr.vcf.gz']\n", "parameter: walltime = '24h'\n", - "# This file can be downloaded from https://ftp.ncbi.nlm.nih.gov/snp/organisms//human_9606_b150_GRCh38p7/VCF/00-All.vcf.gz.\n", + "# This file can be downloaded from https://ftp.ncbi.nlm.nih.gov/snp/organisms/human_9606_b150_GRCh38p7/VCF/00-All.vcf.gz.\n", "input: f'{filename}.vcf.gz'\n", "output: f'{_input:nn}.add_chr.vcf.gz'\n", "task: trunk_workers = 1, trunk_size = job_size, walltime = walltime, mem = mem, cores = numThreads, tags = f'{step_name}_{_output:bn}'\n", @@ -501,7 +501,7 @@ { "cell_type": "code", "execution_count": null, - "id": "hydraulic-robert", + "id": "scenic-chart", "metadata": { "kernel": "SoS" }, @@ -532,7 +532,7 @@ }, { "cell_type": "markdown", - "id": "above-thunder", + "id": "increased-complaint", "metadata": { "kernel": "SoS" }, @@ -545,7 +545,7 @@ { "cell_type": "code", "execution_count": 4, - "id": "integral-equity", + "id": "neither-liberty", "metadata": { "kernel": "SoS" }, @@ -594,7 +594,7 @@ }, { "cell_type": "markdown", - "id": "after-pendant", + "id": "needed-mitchell", "metadata": { "kernel": "SoS" }, @@ -605,7 +605,7 @@ { "cell_type": "code", "execution_count": 3, - "id": "infrared-composition", + "id": "southeast-garlic", "metadata": { "kernel": "SoS" }, @@ -671,7 +671,7 @@ }, { "cell_type": "markdown", - "id": "scheduled-alcohol", + "id": "driven-mills", "metadata": { "kernel": "SoS" }, @@ -686,7 +686,7 @@ { "cell_type": "code", "execution_count": null, - "id": "vocal-legislature", + "id": "quick-windsor", "metadata": { "kernel": "SoS" }, @@ -715,7 +715,7 @@ { "cell_type": "code", "execution_count": null, - "id": "professional-brunswick", + "id": "still-basketball", "metadata": { "kernel": "SoS" }, diff --git a/_sources/code/data_preprocessing/phenotype/gene_annotation.ipynb b/_sources/code/data_preprocessing/phenotype/gene_annotation.ipynb index 9565a3d3e..8a003e029 100644 --- a/_sources/code/data_preprocessing/phenotype/gene_annotation.ipynb +++ b/_sources/code/data_preprocessing/phenotype/gene_annotation.ipynb @@ -914,7 +914,7 @@ "sos" ] ], - "version": "0.24.1" + "version": "0.24.0" } }, "nbformat": 4, diff --git a/_sources/code/molecular_phenotypes/calling/RNA_calling.ipynb b/_sources/code/molecular_phenotypes/calling/RNA_calling.ipynb index a33cb2ec1..8d6733141 100644 --- a/_sources/code/molecular_phenotypes/calling/RNA_calling.ipynb +++ b/_sources/code/molecular_phenotypes/calling/RNA_calling.ipynb @@ -917,6 +917,113 @@ " samtools index ${_output[0]}" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "af6a50c2-baed-4f40-a573-88b74a9e9b67", + "metadata": { + "kernel": "SoS" + }, + "outputs": [], + "source": [ + "[STAR_sQTL_align_1]\n", + "# Reference gene model\n", + "parameter: gtf = path\n", + "# STAR indexing file\n", + "parameter: STAR_index = path\n", + "parameter: outFilterMultimapNmax = 20 \n", + "parameter: alignSJoverhangMin = 8 \n", + "parameter: alignSJDBoverhangMin = 1 \n", + "parameter: outFilterMismatchNmax = 999 \n", + "parameter: outFilterMismatchNoverLmax = 0.1\n", + "parameter: alignIntronMin = 20 \n", + "parameter: alignIntronMax = 1000000 \n", + "parameter: alignMatesGapMax = 1000000 \n", + "parameter: outFilterType = \"BySJout\" \n", + "parameter: outFilterScoreMinOverLread = 0.33 \n", + "parameter: outFilterMatchNminOverLread = 0.33 \n", + "parameter: limitSjdbInsertNsj = 1200000 \n", + "parameter: outSAMstrandField = \"intronMotif\" \n", + "parameter: outFilterIntronMotifs = \"None\" \n", + "parameter: alignSoftClipAtReferenceEnds = \"Yes\" \n", + "parameter: quantMode = [\"TranscriptomeSAM\", \"GeneCounts\"]\n", + "parameter: outSAMattrRGline = [\"ID:rg1\", \"SM:sm1\"]\n", + "parameter: outSAMattributes = [\"NH\", \"HI\", \"AS\", \"nM\", \"NM\", \"ch\"] \n", + "parameter: chimSegmentMin = 15 \n", + "parameter: chimJunctionOverhangMin = 15 \n", + "parameter: chimOutType = [\"Junctions\", \"WithinBAM\", \"SoftClip\"]\n", + "parameter: chimMainSegmentMultNmax = 1 \n", + "parameter: sjdbOverhang = 100\n", + "parameter: wasp_VCF = path\n", + "if int(mem.replace(\"G\",\"\")) < 40:\n", + " print(\"Insufficent memory for STAR, changing to 40G\")\n", + " star_mem = '40G'\n", + "else:\n", + " star_mem = mem\n", + "# This option is commented out because it will force the downstream analysis to use 40G, which significantlly slow down the process.\n", + "input: fastq,group_by = is_paired_end + 1,group_with = {\"sample_id\",\"read_length\"}\n", + "output: cord_bam = f'{cwd}/{_sample_id}.Aligned.sortedByCoord.out.bam',\n", + " trans_bam = f'{cwd}/{_sample_id}.Aligned.toTranscriptome.out.bam'\n", + "if _read_length == 0:\n", + " print(\"Using specified --sjdbOverhang as read length\")\n", + "else:\n", + " print(\"Using read length specified in the sample list\")\n", + "task: trunk_workers = 1, trunk_size = job_size, walltime = walltime, mem = star_mem, cores = numThreads\n", + "bash: container=container, expand= \"${ }\", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout'\n", + " rm -rf ${cwd}/${_sample_id}.*.out.*.gz\n", + " rm -rf ${cwd}/${_sample_id}._STARpass1\n", + " set -e\n", + " touch ${_output[0]:n}.star_start.timestamp\n", + " STAR --runMode alignReads \\\n", + " --runThreadN ${numThreads} \\\n", + " --genomeDir ${STAR_index} \\\n", + " --readFilesIn ${_input:r} \\\n", + " --readFilesCommand ${\"cat\" if uncompressed else \"zcat\"} \\\n", + " --outFileNamePrefix ${_output[0]:nnnn}. \\\n", + " --outSAMstrandField ${outSAMstrandField} \\\n", + " --twopassMode Basic \\\n", + " --outFilterMultimapNmax ${outFilterMultimapNmax} \\\n", + " --alignSJoverhangMin ${alignSJoverhangMin} \\\n", + " --alignSJDBoverhangMin ${alignSJDBoverhangMin} \\\n", + " --outFilterMismatchNmax ${outFilterMismatchNmax} \\\n", + " --outFilterMismatchNoverLmax ${outFilterMismatchNoverLmax} \\\n", + " --alignIntronMin ${alignIntronMin} \\\n", + " --alignIntronMax ${alignIntronMax} \\\n", + " --alignMatesGapMax ${alignMatesGapMax} \\\n", + " --outFilterType ${outFilterType} \\\n", + " --outFilterScoreMinOverLread ${outFilterScoreMinOverLread} \\\n", + " --outFilterMatchNminOverLread ${outFilterMatchNminOverLread} \\\n", + " --limitSjdbInsertNsj ${limitSjdbInsertNsj} \\\n", + " --outFilterIntronMotifs ${outFilterIntronMotifs} \\\n", + " --alignSoftClipAtReferenceEnds ${alignSoftClipAtReferenceEnds} \\\n", + " --quantMode ${\" \".join(quantMode)} \\\n", + " --outSAMtype BAM Unsorted \\\n", + " --outSAMunmapped Within \\\n", + " --genomeLoad NoSharedMemory \\\n", + " --chimSegmentMin ${chimSegmentMin} \\\n", + " --chimJunctionOverhangMin ${chimJunctionOverhangMin} \\\n", + " --chimOutType ${\" \".join(chimOutType)} \\\n", + " --chimMainSegmentMultNmax ${chimMainSegmentMultNmax} \\\n", + " --chimOutJunctionFormat 0 \\\n", + " --outSAMattributes ${\" \".join(outSAMattributes)} \\\n", + " --outSAMattrRGline ${\" \".join(outSAMattrRGline)} \\\n", + " --sjdbOverhang ${sjdbOverhang if _read_length == 0 else _read_length } \\\n", + " --sjdbGTFfile ${gtf} \\\n", + " --varVCFfile <(zcat ${wasp_VCF}) \\\n", + " --waspOutputMode SAMtag \\\n", + "\n", + " rm -r ${_output[0]:nnnn}._STARgenome\n", + " ${ f'rm -rf {_output[0]:nnnn}._STARtmp' if is_paired_end else \"\"}\n", + " touch ${_output[0]:n}.sort_start.timestamp\n", + " samtools sort --threads ${numThreads} -o ${_output[0]:nnnn}.Aligned.sortedByCoord.out.bam ${_output[0]:nnnn}.Aligned.out.bam # According to GTEX, this can help reducing the amount of memory consumption.\n", + " rm ${_output[0]:nnnn}.Aligned.out.bam \n", + " samtools view -h -q 255 ${_output[0]} | grep -v \"vW:i:[2-7]\" | samtools view -b > ${_output[0]:n}.filtered.bam\n", + " samtools view -h -q 255 ${_output[1]} | grep -v \"vW:i:[2-7]\" | samtools view -b > ${_output[1]:n}.filtered.bam\n", + "\n", + " samtools index ${_output[0]}\n", + "\n" + ] + }, { "cell_type": "markdown", "id": "716aec5b-2ddd-432e-82e3-639945cbc809", @@ -1775,7 +1882,7 @@ "sos" ] ], - "version": "0.24.1" + "version": "0.24.0" } }, "nbformat": 4, diff --git a/code/data_preprocessing/genotype/GWAS_QC.html b/code/data_preprocessing/genotype/GWAS_QC.html index 98c22b6f2..adfa951a4 100644 --- a/code/data_preprocessing/genotype/GWAS_QC.html +++ b/code/data_preprocessing/genotype/GWAS_QC.html @@ -662,7 +662,7 @@

FunGen-xQTL Consortium

@@ -979,7 +979,7 @@

Estimate kinship in the sampleparameter: maximize_unrelated = False output: f'{_input:n}.related_id' task: trunk_workers = 1, trunk_size = job_size, walltime = walltime, mem = mem, cores = numThreads, tags = f'{step_name}_{_output:bn}' -R: container=container, expand= "${ }", stderr = f'{_output}.stderr', stdout = f'{_output}.stdout' +R: container=container, expand= "${ }", stderr = f'{_output}.stderr', stdout = f'{_output}.stdout', entrypoint=entrypoint library(dplyr) library(igraph) # Remove related individuals while keeping maximum number of individuals @@ -1164,15 +1164,15 @@

Estimate kinship in the samplecat("There are", nrow(dat),"related individuals using a kinship threshold of ${kinship}\n") write.table(dat,${_output:r}, quote=FALSE, row.names=FALSE, col.names=FALSE) -bash: expand= "$[ ]", stderr = f'{_output}.stderr', stdout = f'{_output}.stdout', container = container - stdout=$[_output].stdout - for i in $[_output] ; do - echo "output_info: $i " >> $stdout; - echo "output_size:" `ls -lh $i | cut -f 5 -d " "` >> $stdout; - echo "output_rows:" `zcat $i | wc -l | cut -f 1 -d " "` >> $stdout; - echo "output_column:" `zcat $i | head -1 | wc -w ` >> $stdout; - echo "output_preview:" >> $stdout; - cat $i | grep -v "##" | head | cut -f 1,2,3,4,5,6 >> $stdout ; done +bash: expand= "${ }", stderr = f'{_output:n}.stderr', stdout = f'{_output}.stdout', container = container, entrypoint=entrypoint + i="${_output}" + output_size=$(ls -lh $i | cut -f 5 -d ' ') + output_rows=$(zcat $i | wc -l | cut -f 1 -d ' ') + output_column=$(zcat $i | head -1 | wc -w) + output_preview=$(cat $i | grep -v "##" | head | cut -f 1,2,3,4,5,6) + + printf "output_info: %s\noutput_size: %s\noutput_rows: %s\noutput_column: %s\noutput_preview:\n%s\n" \ + "$i" "$output_size" "$output_rows" "$output_column" "$output_preview" >> ${_output}.stdout @@ -1187,7 +1187,7 @@

Estimate kinship in the samplerelated_id = [x.strip() for x in open(_input[0]).readlines()] stop_if(len(related_id) == 0) task: trunk_workers = 1, trunk_size = job_size, walltime = walltime, mem = mem, cores = numThreads, tags = f'{step_name}_{_output[0]:bn}' -bash: expand= "${ }", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', container = container +bash: expand= "${ }", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', container = container, entrypoint=entrypoint plink2 \ --bfile ${_input[1]:n} \ --remove ${_input[0]} \ @@ -1205,12 +1205,11 @@

Estimate kinship in the sample--threads ${numThreads} \ --memory ${int(expand_size(mem) * 0.9)/1e6} --new-id-max-allele-len 1000 --set-all-var-ids chr@:#_\$r_\$a -bash: expand= "$[ ]", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', container = container - stdout=$[_output[0]:n].stdout - for i in $[_output] ; do - echo "output_info: $i " >> $stdout; - echo "output_size:" `ls -lh $i | cut -f 5 -d " "` >> $stdout; - done +bash: expand= "${ }", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', container = container, entrypoint=entrypoint + for i in ${_output}; do + output_size=$(ls -lh $i | cut -f 5 -d ' ') + printf "output_info: %s\noutput_size: %s\n" "$i" "$output_size" >> ${_output[0]:n}.stdout + done @@ -1253,7 +1252,7 @@

Genotype and sample QCinput: genoFile, group_by=1 output: f'{cwd}/{_input:bn}{("."+name) if name else ""}.plink_qc{".extracted" if keep_variants.is_file() else ""}{".bed" if not meta_only else ".snplist"}' task: trunk_workers = 1, trunk_size = job_size, walltime = walltime, mem = mem, cores = numThreads, tags = f'{step_name}_{_output:bn}' -bash: container=container, volumes=[f'{cwd}:{cwd}'], expand= "${ }", stderr = f'{_output:n}.stderr', stdout = f'{_output:n}.stdout' +bash: container=container, volumes=[f'{cwd}:{cwd}'], expand= "${ }", stderr = f'{_output:n}.stderr', stdout = f'{_output:n}.stdout', entrypoint=entrypoint plink2 \ --bfile ${_input:n} \ ${('--maf %s' % maf_filter) if maf_filter > 0 else ''} \ @@ -1274,12 +1273,10 @@

Genotype and sample QC--threads ${numThreads} \ --memory ${int(expand_size(mem) * 0.9)/1e6} --new-id-max-allele-len 1000 --set-all-var-ids chr@:#_\$r_\$a -bash: expand= "$[ ]", stderr = f'{_output:n}.stderr', stdout = f'{_output:n}.stdout', container = container - stdout=$[_output:n].stdout - for i in $[_output] ; do - echo "output_info: $i " >> $stdout; - echo "output_size:" `ls -lh $i | cut -f 5 -d " "` >> $stdout; - done +bash: expand= "${ }", stderr = f'{_output:n}.stderr', stdout = f'{_output:n}.stdout', container = container, entrypoint=entrypoint + i="${_output}" + output_size=$(ls -lh $i | cut -f 5 -d ' ') + printf "output_info: %s\noutput_size: %s\n" "$i" "$output_size" >> ${_output:n}.stdout @@ -1297,7 +1294,7 @@

Genotype and sample QCstop_if(r2==0) output: bed=f'{cwd}/{_input:bn}.prune.bed', prune=f'{cwd}/{_input:bn}.prune.in' task: trunk_workers = 1, trunk_size = job_size, walltime = walltime, mem = mem, cores = numThreads, tags = f'{step_name}_{_output[0]:bn}' -bash: container=container, expand= "${ }", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout' +bash: container=container, expand= "${ }", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', entrypoint=entrypoint plink2 \ --bfile ${_input:n} \ --indep-pairwise ${window} ${shift} ${r2} \ @@ -1313,19 +1310,17 @@

Genotype and sample QC--threads ${numThreads} \ --memory ${int(expand_size(mem) * 0.9)/1e6} -bash: expand= "$[ ]", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', container = container - stdout=$[_output[0]:n].stdout - for i in $[_output[0]] ; do - echo "output_info: $i " >> $stdout; - echo "output_size:" `ls -lh $i | cut -f 5 -d " "` >> $stdout; - done - for i in $[_output[1]] ; do - echo "output_info $i " >> $stdout; - echo "output_size:" `ls -lh $i | cut -f 5 -d " "` >> $stdout; - echo "output_rows:" `zcat $i | wc -l | cut -f 1 -d " "` >> $stdout; - echo "output_column:" `zcat $i | head -1 | wc -w ` >> $stdout; - echo "output_preview:" >> $stdout; - zcat $i | head | cut -f 1,2,3,4,5,6 >> $stdout ; done +bash: expand= "${ }", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout', container = container, entrypoint=entrypoint + i="${_output[0]}" + output_size=$(ls -lh $i | cut -f 5 -d ' ') + printf "output_info: %s\noutput_size: %s\n" "$i" "$output_size" >> ${_output[0]:n}.stdout + i="${_output[1]}" + output_size=$(ls -lh $i | cut -f 5 -d ' ') + output_rows=$(zcat $i | wc -l | cut -f 1 -d ' ') + output_column=$(zcat $i | head -1 | wc -w) + output_preview=$(cat $i | grep -v "##" | head | cut -f 1,2,3,4,5,6) + printf "output_info: %s\noutput_size: %s\noutput_rows: %s\noutput_column: %s\noutput_preview:\n%s\n" \ + "$i" "$output_size" "$output_rows" "$output_column" "$output_preview" >> ${_output[1]}.stdout diff --git a/code/data_preprocessing/genotype/VCF_QC.html b/code/data_preprocessing/genotype/VCF_QC.html index da087873c..fb1f4c002 100644 --- a/code/data_preprocessing/genotype/VCF_QC.html +++ b/code/data_preprocessing/genotype/VCF_QC.html @@ -760,17 +760,17 @@

Minimal working exampleand was stored here: https://drive.google.com/file/d/1sxxPdPIyKma0mAl8TKwhgyRHlOh0Oyrc/view?usp=sharing

FIXME: point this to the synapse folder.

The MWE was used as follows:

-
sos run pipeline/VCF_QC.ipynb rename_chrs \
+
sos run VCF_QC.ipynb rename_chrs \
     --genoFile reference_data/00-All.vcf.gz \
     --cwd reference_data --container bioinfo.sif
 

 

-
sos run pipeline/VCF_QC.ipynb dbsnp_annotate \
+
sos run VCF_QC.ipynb dbsnp_annotate \
     --genoFile reference_data/00-All.add_chr.vcf.gz \
     --cwd reference_data --container bioinfo.sif
 

 

-
sos run pipeline/VCF_QC.ipynb qc    \
+
sos run VCF_QC.ipynb qc    \
     --genoFile data/MWE/MWE_genotype.vcf     \
     --dbsnp-variants data/reference_data/00-All.add_chr.variants.gz  \
     --reference-genome data/reference_data/GRCh38_full_analysis_set_plus_decoy_hla.noALT_noHLA_noDecoy_ERCC.fasta   \
@@ -778,7 +778,7 @@ 
Minimal working example

 

 
To run in parallel for all genotype data listed in mwe_genotype_list,

-
sos run pipeline/VCF_QC.ipynb qc    \
+
sos run VCF_QC.ipynb qc    \
     --genoFile data/mwe/mwe_genotype_list    \
     --dbsnp-variants data/reference_data/00-All.add_chr.variants.gz  \
     --reference-genome data/reference_data/GRCh38_full_analysis_set_plus_decoy_hla.noALT_noHLA_noDecoy_ERCC.fasta   \
@@ -1006,7 +1006,7 @@ 
Annotate known and novel variants
 
[rename_chrs: provides = '{filename}.add_chr.vcf.gz']
 parameter: walltime = '24h'
-# This file can be downloaded from https://ftp.ncbi.nlm.nih.gov/snp/organisms//human_9606_b150_GRCh38p7/VCF/00-All.vcf.gz.
+# This file can be downloaded from https://ftp.ncbi.nlm.nih.gov/snp/organisms/human_9606_b150_GRCh38p7/VCF/00-All.vcf.gz.
 input: f'{filename}.vcf.gz'
 output: f'{_input:nn}.add_chr.vcf.gz'
 task: trunk_workers = 1, trunk_size = job_size, walltime = walltime, mem = mem, cores = numThreads, tags = f'{step_name}_{_output:bn}'
diff --git a/code/molecular_phenotypes/calling/RNA_calling.html b/code/molecular_phenotypes/calling/RNA_calling.html
index 17401cda0..149554218 100644
--- a/code/molecular_phenotypes/calling/RNA_calling.html
+++ b/code/molecular_phenotypes/calling/RNA_calling.html
@@ -1507,6 +1507,107 @@ 
Step Outputs
 

+
[STAR_sQTL_align_1]
+# Reference gene model
+parameter: gtf = path
+# STAR indexing file
+parameter: STAR_index = path
+parameter: outFilterMultimapNmax = 20 
+parameter: alignSJoverhangMin = 8 
+parameter: alignSJDBoverhangMin = 1 
+parameter: outFilterMismatchNmax = 999 
+parameter: outFilterMismatchNoverLmax = 0.1
+parameter: alignIntronMin = 20 
+parameter: alignIntronMax = 1000000 
+parameter: alignMatesGapMax = 1000000 
+parameter: outFilterType =  "BySJout" 
+parameter: outFilterScoreMinOverLread = 0.33 
+parameter: outFilterMatchNminOverLread = 0.33 
+parameter: limitSjdbInsertNsj = 1200000 
+parameter: outSAMstrandField = "intronMotif" 
+parameter: outFilterIntronMotifs = "None" 
+parameter: alignSoftClipAtReferenceEnds = "Yes" 
+parameter: quantMode = ["TranscriptomeSAM", "GeneCounts"]
+parameter: outSAMattrRGline = ["ID:rg1", "SM:sm1"]
+parameter: outSAMattributes = ["NH", "HI", "AS", "nM", "NM", "ch"] 
+parameter: chimSegmentMin = 15 
+parameter: chimJunctionOverhangMin = 15 
+parameter: chimOutType = ["Junctions", "WithinBAM", "SoftClip"]
+parameter: chimMainSegmentMultNmax = 1 
+parameter: sjdbOverhang = 100
+parameter: wasp_VCF = path
+if int(mem.replace("G","")) <  40:
+    print("Insufficent memory for STAR, changing to 40G")
+    star_mem = '40G'
+else:
+    star_mem = mem
+# This option is commented out because it will force the downstream analysis to use 40G, which significantlly slow down the process.
+input: fastq,group_by = is_paired_end + 1,group_with = {"sample_id","read_length"}
+output: cord_bam = f'{cwd}/{_sample_id}.Aligned.sortedByCoord.out.bam',
+        trans_bam = f'{cwd}/{_sample_id}.Aligned.toTranscriptome.out.bam'
+if _read_length == 0:
+    print("Using specified --sjdbOverhang as read length")
+else:
+    print("Using read length specified in the sample list")
+task: trunk_workers = 1, trunk_size = job_size, walltime = walltime, mem = star_mem, cores = numThreads
+bash: container=container, expand= "${ }", stderr = f'{_output[0]:n}.stderr', stdout = f'{_output[0]:n}.stdout'
+    rm -rf ${cwd}/${_sample_id}.*.out.*.gz
+    rm -rf ${cwd}/${_sample_id}._STARpass1
+    set -e
+    touch ${_output[0]:n}.star_start.timestamp
+    STAR --runMode alignReads \
+        --runThreadN ${numThreads} \
+        --genomeDir  ${STAR_index} \
+        --readFilesIn  ${_input:r} \
+        --readFilesCommand ${"cat" if uncompressed else "zcat"} \
+        --outFileNamePrefix ${_output[0]:nnnn}. \
+        --outSAMstrandField ${outSAMstrandField} \
+        --twopassMode Basic \
+        --outFilterMultimapNmax ${outFilterMultimapNmax} \
+        --alignSJoverhangMin ${alignSJoverhangMin} \
+        --alignSJDBoverhangMin ${alignSJDBoverhangMin} \
+        --outFilterMismatchNmax ${outFilterMismatchNmax} \
+        --outFilterMismatchNoverLmax ${outFilterMismatchNoverLmax} \
+        --alignIntronMin ${alignIntronMin} \
+        --alignIntronMax ${alignIntronMax} \
+        --alignMatesGapMax ${alignMatesGapMax} \
+        --outFilterType ${outFilterType} \
+        --outFilterScoreMinOverLread ${outFilterScoreMinOverLread} \
+        --outFilterMatchNminOverLread ${outFilterMatchNminOverLread} \
+        --limitSjdbInsertNsj ${limitSjdbInsertNsj} \
+        --outFilterIntronMotifs ${outFilterIntronMotifs} \
+        --alignSoftClipAtReferenceEnds ${alignSoftClipAtReferenceEnds} \
+        --quantMode ${" ".join(quantMode)} \
+        --outSAMtype BAM Unsorted \
+        --outSAMunmapped Within \
+        --genomeLoad NoSharedMemory \
+        --chimSegmentMin ${chimSegmentMin} \
+        --chimJunctionOverhangMin ${chimJunctionOverhangMin} \
+        --chimOutType ${" ".join(chimOutType)} \
+        --chimMainSegmentMultNmax ${chimMainSegmentMultNmax} \
+        --chimOutJunctionFormat 0 \
+        --outSAMattributes ${" ".join(outSAMattributes)} \
+        --outSAMattrRGline ${" ".join(outSAMattrRGline)} \
+        --sjdbOverhang ${sjdbOverhang if _read_length == 0 else _read_length  } \
+        --sjdbGTFfile ${gtf} \
+        --varVCFfile <(zcat ${wasp_VCF}) \
+        --waspOutputMode SAMtag \
+
+    rm -r ${_output[0]:nnnn}._STARgenome
+    ${ f'rm -rf {_output[0]:nnnn}._STARtmp' if is_paired_end else ""}
+    touch ${_output[0]:n}.sort_start.timestamp
+    samtools sort --threads ${numThreads} -o ${_output[0]:nnnn}.Aligned.sortedByCoord.out.bam ${_output[0]:nnnn}.Aligned.out.bam # According to GTEX, this can help reducing the amount of memory consumption.
+    rm ${_output[0]:nnnn}.Aligned.out.bam 
+    samtools view -h -q 255 ${_output[0]} | grep -v "vW:i:[2-7]" | samtools view -b > ${_output[0]:n}.filtered.bam
+    samtools view -h -q 255 ${_output[1]} | grep -v "vW:i:[2-7]" | samtools view -b > ${_output[1]:n}.filtered.bam
+
+    samtools index ${_output[0]}
+

+

+

+

+

+

 
[strand_detected_1: shared="step_strand_detected"]
 input: output_from("STAR_align_1")["trans_bam"], group_with = "sample_id"
 import pandas as pd
diff --git a/searchindex.js b/searchindex.js
index 3f39a53be..a4c231785 100644
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
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5,18,19,20,23,32,34,37],eqtl_1:25,eqtl_2:25,eqtl_3:25,eqtl_analysis_command:6,eqtl_analysis_externalb:[],eqtl_annot1:25,eqtl_annot2:25,eqtl_annot3:25,eqtl_annot:[24,25],eqtl_annot_comb:25,eqtl_annot_rsid:24,eqtl_command:[3,9,15,18],eqtl_id:25,eqtl_pip:25,eqtl_prepare_express:34,eqtl_summary_fil:45,eqtl_sumstat:25,eqtl_z1:24,eqtl_z2:24,eqtl_z3:24,eqtlqc:33,equal:[19,37,38],equal_sampl:45,equal_spac:45,equat:29,equilibrium:[11,12,13],equival:12,ercc92:[5,19],ercc:[5,16,19,37,38,39,44],ercc_:19,ercc_control:19,ercc_gtf:19,ercc_refer:19,error:[1,2,12,20,21,24,25,26,31,32,38,45,49],error_cach:20,es:[20,31,32,49],est:28,establish:46,estim:[3,9,15,17,20,24,25,26,29,31,32,38,49],estimate_null_correlation_simpl:46,estimate_prior:24,estimate_prior_method:20,estimate_prior_vari:20,estimate_residual_vari:[20,21],estimate_rspd:38,estimated_library_s:38,et:[29,33,38,41,46,47],etc:[2,5,9,11,14,29,38],ethnic:12,eur:28,european:28,evalu:[12,13],even:[13,16,19,34,48],event:[13,19,32,35,39,41,51],event_typ:35,eventtyp:41,everi:[11,13,33],everyth:[19,40],everywher:11,evid:[1,2],ex:5,exact:[13,15,32],exact_match:25,exactli:[38,44],examin:[12,15],exampl:[0,5,15,29,36,45,46,51],example_cov:[],example_data:26,example_script:5,except:[12,19,28,32,35,45],exchang:46,excis:41,exclud:[1,6,10,11,12,13,19,33,35,45,46,48],exclude_condit:[46,48],exclude_vari:11,exclus:[19,41],excut:[5,6],excute_metal_script:49,exe_dir:[4,5,6,24,26],exec:19,execut:[4,11,28,38,39,45,46,51],exist:[1,16,20,21,26,32,34,35,38,39,41,45],exit:[33,35],exom:11,exon:[16,19,32,41],exon_df:16,exon_gtf:19,exon_intron_extractor:39,exon_list:16,exon_numb:19,exon_read:38,exon_readscount:[5,38],exon_t:16,exongetrinfo:5,exoninfo:5,exons_chr:16,exons_t:16,exp:[21,28,33,40],expand:[0,1,2,4,5,6,7,8,10,11,12,13,14,16,17,19,20,21,25,26,28,29,31,32,33,34,35,38,39,40,41,45,46,47,49],expand_s:[10,11,13,14,19,20,35,38,41],expandus:28,expect:[4,7,8,10,11,12,13,14,15,16,17,19,20,21,28,29,33,34,35,38,40,41],expected_count:38,experi:[9,11],explain:[3,6,9,12,15,16,19,29,38,46],explan:[0,13,38],explanari:46,explicitli:[16,34],explict:40,explor:[13,15],exppersampl:33,expr:[5,33],express:[3,6,12,15,16,18,33,34,51],expression_b:2,expression_norm:[],exptdata:[20,31,49],extend:[29,38,45],extens:[10,33,51],extent:0,extern:[8,15],extra:[13,14,15],extra_arg:28,extra_fn_clean_ext:38,extract:[2,6,8,9,12,13,16,17,19,20,37,38,41,46,47],extract_effect:[47,48],extract_snpvar:26,extract_total_read:39,extraction_sample_list:8,ey:21,ez:[22,46,47,48],f08080:12,f0:47,f1:[13,46],f4a460:12,f7:21,f98ab7dea176f42cb61b80450b795ef19b329e8eb715b87b0d13c2a0854d:14,f:[1,2,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,21,23,24,25,26,28,31,32,33,34,35,37,38,39,40,41,45,46,47,48,49],f_gwa:25,f_miss:13,f_susie_tad_eqtl:20,f_susie_tad_haqt:23,f_susie_tad_haqtl_po:20,f_susie_tad_haqtl_pos_check_pure_2:[20,23],f_susie_tad_haqtl_pos_check_pure_3:23,f_susie_tad_haqtl_pos_limited_2:23,f_susie_tad_haqtl_pos_resum:23,f_susie_tad_haqtl_resum:23,f_susie_tad_meqtl_pos_2:23,f_susie_tad_meqtl_pos_check_pur:23,f_susie_tad_meqtl_pos_limited_2:23,f_susie_tad_meqtl_pos_resum:23,fa:[5,13,19,38,46,47],facil:0,fact:[1,12,29,39],factor:[1,2,8,12,20,29,33,34],factor_:8,factor_and_covari:[],factor_covari:[],factor_n:[],factor_opt:6,factorfil:[6,8,9],factorvector:21,fai:19,faidx:19,fail:[11,20,40],fail_ibd:11,fail_if:[11,28,45,46,47],fail_inord:11,fail_inrevers:11,failid:11,failids_multipl:11,failids_singl:11,failure_ct:45,fairli:46,fake:[7,32],fake_vcf:7,fall:[28,38],fals:[1,2,3,4,6,7,8,10,11,12,13,14,16,19,20,21,28,32,33,35,38,39,40,41,45,46,47],fam138a:16,fam:[2,6,11,12,14,15],famili:[11,12,15,20,21],familiar:[0,12,45],fanni:0,far:[7,33],fasqp:[],fast:[],fast_trim_adaptor:44,fasta:[3,5,6,13,15,32,37,38,44],fasta_with_adapters_etc:[5,38],fasteqtl:45,faster:[38,45,46],fastp_trim_adaptor:[37,38,44],fastp_trim_adaptor_1:38,fastp_trim_adaptor_2:38,fastq1:38,fastq2:38,fastq:[17,37,38,41,44],fastqc:38,fastqc_data:[],fastqlist:[37,38,44],fastqtl:[24,32,45,46],fastqtl_to_mash:[45,46],fastqtl_to_mash_output:[45,46],fastqtlsumstat:[45,46],fault:35,fc8d59:47,fc:35,fd:14,fdr:[2,32],fdr_beta:2,fdr_beta_0:2,fdr_perm:2,fdr_perm_0:2,featur:[0,2,16,26,28,33,35,38,39,40],featurenam:40,features_nam:[],fed:[5,8,17,37,44,48],fee090:47,feed:17,feng:0,fetaldhs_trynka:28,fetch:[],few:[0,12,28,33,38,47],fewer:20,ff0000:12,ff00ff:12,ff1493:12,ff6347:12,ff69b4:12,ff8c00:12,ffa07a:12,ffc0cb:12,ffe4c4:12,ffff00:12,ffff54:12,ffffbf:47,fg:[],fgc:0,fid1:11,fid2:11,fid:[11,12,14],field:[13,32,49],field_out:39,figur:[5,38,45],file1:39,file:[0,1,2,3,4,5,6,7,8,9,12,16,18,20,21,31,33,34,35,37,38,40,41,42,44,45,46,47,48,49,51],file_dict:4,file_inv:[1,2,32,35,38],file_nam:41,file_target:[46,47],filed:[7,31,32],filedir:39,fileformat:[7,20,31,32,49],filenam:[4,5,10,13,14,17,21,28,31,38,41,44,45,47],filenotfounderror:28,filepath_or_buff:19,fill:[9,12,13,19,35,38,41,42,46,47],fill_diagon:21,fillna:[35,41],filter:[2,3,6,7,8,9,11,12,15,16,19,20,21,23,25,31,32,33,35,38,39,40,45,49],filter_:1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Computational Protocol","APEX QTL association testing","TensorQTL QTL association testing","cisQTL analysis workflows","transQTL analysis workflows","RNA-seq calling and QC","Univariate xQTL Discovery","Factor analysis using Bi-Cross validation","Covariate data formatting","Covariate data preprocessing","Genomic relationship matrices","Genotype PLINK file quality control","Principal component analysis","Genotype VCF file quality control","Genotype data formatting","Genotype data preprocessing","Gene coordinate annotation","Phenotype data formatting","Phenotype data preprocessing","Reference data standardization","Fine-mapping with SuSiE model","Fine-mapping with SuSiE RSS model","Multivariate fine-mapping workflows","Univariate fine-mapping workflows","Colocalization with FastENLOC","Multivariate SuSiE and ENLOC model","Fine-mapping with PolyFun","QTL and GWAS Colocalization","Enrichment analysis: TORUS and GREGOR","Stratified LD Score Regression","Functional annotation integration","Summary statistics in VCF format","Summary statistics standardization and export","Sample level RNA-seq quality control","Bulk RNA-seq counts normalization","Normalization and phenotype table generation for splicingQTL analysis","Alternative polyadenylation","RNA-seq expression","Quantifying expression from RNA-seq data","APA Calling","Quantification of methylation data","Quantifying alternative splicing from RNA-seq data","Methylation","scRNA-seq expression calling","Alternative splicing from RNA-seq data","eQTL summary statistics formatting","Data overview","A multivariate EBNM approach for mixture multivariate distribution estimate","Multivariate association with MASH","Meta-analysis with METAL","Meta-analysis with METAL","Illustration of xQTL 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9,15,18,19,20,23,32,34,37],eqtl_1:25,eqtl_2:25,eqtl_3:25,eqtl_analysis_command:6,eqtl_analysis_externalb:[],eqtl_annot1:25,eqtl_annot2:25,eqtl_annot3:25,eqtl_annot:[24,25],eqtl_annot_comb:25,eqtl_annot_rsid:24,eqtl_command:[3,9,15,18],eqtl_id:25,eqtl_pip:25,eqtl_prepare_express:34,eqtl_summary_fil:45,eqtl_sumstat:25,eqtl_z1:24,eqtl_z2:24,eqtl_z3:24,eqtlqc:33,equal:[19,37,38],equal_sampl:45,equal_spac:45,equat:29,equilibrium:[11,12,13],equival:12,ercc92:[5,19],ercc:[5,16,19,37,38,39,44],ercc_:19,ercc_control:19,ercc_gtf:19,ercc_refer:19,error:[1,2,12,20,21,24,25,26,31,32,38,45,49],error_cach:20,es:[20,31,32,49],est:28,establish:46,estim:[3,9,15,17,20,24,25,26,29,31,32,38,49],estimate_null_correlation_simpl:46,estimate_prior:24,estimate_prior_method:20,estimate_prior_vari:20,estimate_residual_vari:[20,21],estimate_rspd:38,estimated_library_s:38,et:[29,33,38,41,46,47],etc:[2,5,9,11,14,29,38],ethnic:12,eur:28,european:28,evalu:[12,13],even:[13,16,19,34,48],event:[13,19,32,35,39,41,51],event_typ:35,eventtyp:41,everi:[11,13,33],everyth:[19,40],everywher:11,evid:[1,2],ex:5,exact:[13,15,32],exact_match:25,exactli:[38,44],examin:[12,15],exampl:[0,5,15,29,36,45,46,51],example_cov:[],example_data:26,example_script:5,except:[12,19,28,32,35,45],exchang:46,excis:41,exclud:[1,6,10,11,12,13,19,33,35,45,46,48],exclude_condit:[46,48],exclude_vari:11,exclus:[19,41],excut:[5,6],excute_metal_script:49,exe_dir:[4,5,6,24,26],exec:19,execut:[4,11,28,38,39,45,46,51],exist:[1,16,20,21,26,32,34,35,38,39,41,45],exit:[33,35],exom:11,exon:[16,19,32,41],exon_df:16,exon_gtf:19,exon_intron_extractor:39,exon_list:16,exon_numb:19,exon_read:38,exon_readscount:[5,38],exon_t:16,exongetrinfo:5,exoninfo:5,exons_chr:16,exons_t:16,exp:[21,28,33,40],expand:[0,1,2,4,5,6,7,8,10,11,12,13,14,16,17,19,20,21,25,26,28,29,31,32,33,34,35,38,39,40,41,45,46,47,49],expand_s:[10,11,13,14,19,20,35,38,41],expandus:28,expect:[4,7,8,10,11,12,13,14,15,16,17,19,20,21,28,29,33,34,35,38,40,41],expected_count:38,experi:[9,11],explain:[3,6,9,12,15,16,19,29,38,46],explan:[0,13,38],explanari:46,explicitli:[16,34],explict:40,explor:[13,15],exppersampl:33,expr:[5,33],express:[3,6,12,15,16,18,33,34,51],expression_b:2,expression_norm:[],exptdata:[20,31,49],extend:[29,38,45],extens:[10,33,51],extent:0,extern:[8,15],extra:[13,14,15],extra_arg:28,extra_fn_clean_ext:38,extract:[2,6,8,9,12,13,16,17,19,20,37,38,41,46,47],extract_effect:[47,48],extract_snpvar:26,extract_total_read:39,extraction_sample_list:8,ey:21,ez:[22,46,47,48],f08080:12,f0:47,f1:[13,46],f4a460:12,f7:21,f98ab7dea176f42cb61b80450b795ef19b329e8eb715b87b0d13c2a0854d:14,f:[1,2,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,21,23,24,25,26,28,31,32,33,34,35,37,38,39,40,41,45,46,47,48,49],f_gwa:25,f_miss:13,f_susie_tad_eqtl:20,f_susie_tad_haqt:23,f_susie_tad_haqtl_po:20,f_susie_tad_haqtl_pos_check_pure_2:[20,23],f_susie_tad_haqtl_pos_check_pure_3:23,f_susie_tad_haqtl_pos_limited_2:23,f_susie_tad_haqtl_pos_resum:23,f_susie_tad_haqtl_resum:23,f_susie_tad_meqtl_pos_2:23,f_susie_tad_meqtl_pos_check_pur:23,f_susie_tad_meqtl_pos_limited_2:23,f_susie_tad_meqtl_pos_resum:23,fa:[5,13,19,38,46,47],facil:0,fact:[1,12,29,39],factor:[1,2,8,12,20,29,33,34],factor_:8,factor_and_covari:[],factor_covari:[],factor_n:[],factor_opt:6,factorfil:[6,8,9],factorvector:21,fai:19,faidx:19,fail:[11,20,40],fail_ibd:11,fail_if:[11,28,45,46,47],fail_inord:11,fail_inrevers:11,failid:11,failids_multipl:11,failids_singl:11,failure_ct:45,fairli:46,fake:[7,32],fake_vcf:7,fall:[28,38],fals:[1,2,3,4,6,7,8,10,11,12,13,14,16,19,20,21,28,32,33,35,38,39,40,41,45,46,47],fam138a:16,fam:[2,6,11,12,14,15],famili:[11,12,15,20,21],familiar:[0,12,45],fanni:0,far:[7,33],fasqp:[],fast:[],fast_trim_adaptor:44,fasta:[3,5,6,13,15,32,37,38,44],fasta_with_adapters_etc:[5,38],fasteqtl:45,faster:[38,45,46],fastp_trim_adaptor:[37,38,44],fastp_trim_adaptor_1:38,fastp_trim_adaptor_2:38,fastq1:38,fastq2:38,fastq:[17,37,38,41,44],fastqc:38,fastqc_data:[],fastqlist:[37,38,44],fastqtl:[24,32,45,46],fastqtl_to_mash:[45,46],fastqtl_to_mash_output:[45,46],fastqtlsumstat:[45,46],fault:35,fc8d59:47,fc:35,fd:14,fdr:[2,32],fdr_beta:2,fdr_beta_0:2,fdr_perm:2,fdr_perm_0:2,featur:[0,2,16,26,28,33,35,38,39,40],featurenam:40,features_nam:[],fed:[5,8,17,37,44,48],fee090:47,feed:17,feng:0,fetaldhs_trynka:28,fetch:[],few:[0,12,28,33,38,47],fewer:20,ff0000:12,ff00ff:12,ff1493:12,ff6347:12,ff69b4:12,ff8c00:12,ffa07a:12,ffc0cb:12,ffe4c4:12,ffff00:12,ffff54:12,ffffbf:47,fg:[],fgc:0,fid1:11,fid2:11,fid:[11,12,14],field:[13,32,49],field_out:39,figur:[5,38,45],file1:39,file:[0,1,2,3,4,5,6,7,8,9,12,16,18,20,21,31,33,34,35,37,38,40,41,42,44,45,46,47,48,49,51],file_dict:4,file_inv:[1,2,32,35,38],file_nam:41,file_target:[46,47],filed:[7,31,32],filedir:39,fileformat:[7,20,31,32,49],filenam:[4,5,10,13,14,17,21,28,31,38,41,44,45,47],filenotfounderror:28,filepath_or_buff:19,fill:[9,12,13,19,35,38,41,42,46,47],fill_diagon:21,fillna:[35,41],filter:[2,3,6,7,8,9,11,12,15,16,19,20,21,23,25,31,32,33,35,38,39,40,45,49],filter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Computational Protocol","APEX QTL association testing","TensorQTL QTL association testing","cisQTL analysis workflows","transQTL analysis workflows","RNA-seq calling and QC","Univariate xQTL Discovery","Factor analysis using Bi-Cross validation","Covariate data formatting","Covariate data preprocessing","Genomic relationship matrices","Genotype PLINK file quality control","Principal component analysis","Genotype VCF file quality control","Genotype data formatting","Genotype data preprocessing","Gene coordinate annotation","Phenotype data formatting","Phenotype data preprocessing","Reference data standardization","Fine-mapping with SuSiE model","Fine-mapping with SuSiE RSS model","Multivariate fine-mapping workflows","Univariate fine-mapping workflows","Colocalization with FastENLOC","Multivariate SuSiE and ENLOC model","Fine-mapping with PolyFun","QTL and GWAS Colocalization","Enrichment analysis: TORUS and GREGOR","Stratified LD Score Regression","Functional annotation integration","Summary statistics in VCF format","Summary statistics standardization and export","Sample level RNA-seq quality control","Bulk RNA-seq counts normalization","Normalization and phenotype table generation for splicingQTL analysis","Alternative polyadenylation","RNA-seq expression","Quantifying expression from RNA-seq data","APA Calling","Quantification of methylation data","Quantifying alternative splicing from RNA-seq data","Methylation","scRNA-seq expression calling","Alternative splicing from RNA-seq data","eQTL summary statistics formatting","Data overview","A multivariate EBNM approach for mixture multivariate distribution estimate","Multivariate association with MASH","Meta-analysis with METAL","Meta-analysis with METAL","Illustration of xQTL 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