Merge branch 'new.qc.out' into 'develop'

Metadata output update

Closes #56 and #52

See merge request !36

.gitignore

@@ -297,6 +297,8 @@ timeline*.html*
 *.tmp
 *.swp
 *.out
+*_studyRID.json
+*_studyRID.csv
 run*.sh
 
 !.gitkeep

.gitlab-ci.yml

@@ -38,7 +38,8 @@ parseMetadata:
   - stranded=$(singularity run 'docker://bicf/python3:2.0.1_indev' python3 ./workflow/scripts/parseMeta.py -r Replicate_RID -m "./test_data/meta/metaTest.csv" -p stranded)
   - spike=$(singularity run 'docker://bicf/python3:2.0.1_indev' python3 ./workflow/scripts/parseMeta.py -r Replicate_RID -m "./test_data/meta/metaTest.csv" -p spike)
   - species=$(singularity run 'docker://bicf/python3:2.0.1_indev' python3 ./workflow/scripts/parseMeta.py -r Replicate_RID -m "./test_data/meta/metaTest.csv" -p species)
-  - echo -e "${endsMeta},${endsManual},${stranded},${spike},${species},${exp},${study},${rep}" > design.csv
+  - readLength=$(singularity run 'docker://bicf/python3:2.0.1_indev' python3 ./workflow/scripts/parseMeta.py -r Replicate_RID -m "./test_data/meta/metaTest.stageNew.csv" -p readLength)
+  - echo -e "${endsMeta},${endsManual},${stranded},${spike},${species},${readLength},${exp},${study},${rep}" > design.csv
   - pytest -m parseMetadata
 
 inferMetadata:
@@ -66,6 +67,8 @@ trimData:
   script:
   - singularity run 'docker://bicf/trimgalore:1.1' trim_galore --gzip -q 25 --illumina --length 35 --basename Q-Y5F6_1M.se -j 20 ./test_data/fastq/small/Q-Y5F6_1M.R1.fastq.gz
   - singularity run 'docker://bicf/trimgalore:1.1' trim_galore --gzip -q 25 --illumina --length 35 --paired --basename Q-Y5F6_1M.pe -j 20 ./test_data/fastq/small/Q-Y5F6_1M.R1.fastq.gz ./test_data/fastq/small/Q-Y5F6_1M.R2.fastq.gz
+  - readLengthSE=$(zcat *_trimmed.fq.gz | awk '{if(NR%4==2) print length($1)}' | sort -n | awk '{a[NR]=$0}END{print(NR%2==1)?a[int(NR/2)+1]:(a[NR/2]+a[NR/2+1])/2}')
+  - readLengthPE=$(zcat *_1.fq.gz | awk '{if(NR%4==2) print length($1)}' | sort -n | awk '{a[NR]=$0}END{print(NR%2==1)?a[int(NR/2)+1]:(a[NR/2]+a[NR/2+1])/2}')
   - pytest -m trimData
 
 downsampleData:
@@ -104,6 +107,7 @@ countData:
   script:
   - singularity run 'docker://bicf/subread2:2.0.0' featureCounts -T 20 -a /project/BICF/BICF_Core/shared/gudmap/references/GRCh38.p12.v31/genome.gtf -G /project/BICF/BICF_Core/shared/gudmap/references/GRCh38.p12.v31/genome.fna -g 'gene_name' -o Q-Y5F6_1M.se.featureCounts -s 1 -R SAM --primary --ignoreDup ./test_data/bam/small/Q-Y5F6_1M.se.sorted.deduped.bam 
   - singularity run 'docker://bicf/subread2:2.0.0' Rscript ./workflow/scripts/calculateTPM.R --count ./test_data/counts/small/Q-Y5F6_1M.se.featureCounts
+  - assignedReads=$(grep -m 1 'Assigned' *.summary | grep -oe '\([0-9.]*\)')
   - pytest -m makeFeatureCounts
 
 makeBigWig:
@@ -164,7 +168,7 @@ consistency:
   - grep -m 1 \"Assigned\":.[0-9] SE_multiqc_data.json | grep -oe '\([0-9.]*\)' > assignedSE.txt
   - grep -m 1 \"Assigned\":.[0-9] PE_multiqc_data.json | grep -oe '\([0-9.]*\)' > assignedPE.txt
   - echo 7742416 > assignedExpectSE.txt
-  - echo 2599149 > assignedExpectPE.txt
+  - echo 2599140 > assignedExpectPE.txt
   - pytest -m consistencySE
   - pytest -m consistencyPE
   artifacts:

README.md

@@ -58,11 +58,17 @@ FULL EXAMPLE:
 nextflow run workflow/rna-seq.nf --deriva ./data/credential.json --bdbag ./data/cookies.txt --repRID Q-Y5JA
 ```
 
+To run a set of replicates from study RID:
+------------------------------------------
+Run in repo root dir:
+* `sh workflow/scripts/splitStudy.sh [studyRID]`
+It will run in parallel in batches of 5 replicatesRID
 
 
-[**CHANGELOG**](https://git.biohpc.swmed.edu/BICF/gudmap_rbk/rna-seq/blob/develop/CHANGELOG.md)
 
----
+<hr>
+[**CHANGELOG**](https://git.biohpc.swmed.edu/BICF/gudmap_rbk/rna-seq/blob/develop/CHANGELOG.md)
+<hr>
 
 Credits
 =======

cleanup.sh

@@ -5,3 +5,5 @@ rm timeline*.html*
 rm .nextflow*.log*
 rm -r .nextflow/
 rm -r work/
+rm *_studyRID.json
+rm *_studyRID.csv

workflow/conf/multiqc_config.yaml

@@ -70,16 +70,21 @@ custom_data:
     meta:
         file_format: 'tsv'
         section_name: 'Metadata'
-        description: 'This is the comparison of infered metadata and submitter provided'
+        description: 'This is the comparison of infered metadata, submitter provided, and calculated'
         plot_type: 'table'
         pconfig:
             id: 'meta'
+            format: '{:,.0f}'
         headers:
             Source
             Species
             Ends
             Stranded
             Spike-in
+            Raw Reads
+            Assigned Reads
+            Median Read Length
+            Median TIN
     tin:
         file_format: 'tsv'
         section_name: 'TIN'

workflow/rna-seq.nf

@@ -53,6 +53,7 @@ script_bdbagFetch = Channel.fromPath("${baseDir}/scripts/bdbagFetch.sh")
 script_parseMeta = Channel.fromPath("${baseDir}/scripts/parseMeta.py")
 script_inferMeta = Channel.fromPath("${baseDir}/scripts/inferMeta.sh")
 script_calculateTPM = Channel.fromPath("${baseDir}/scripts/calculateTPM.R")
+script_convertGeneSymbols = Channel.fromPath("${baseDir}/scripts/convertGeneSymbols.R")
 script_tinHist = Channel.fromPath("${baseDir}/scripts/tinHist.py")
 
 /*
@@ -237,8 +238,16 @@ process parseMetadata {
     species=\$(python3 ${script_parseMeta} -r ${repRID} -m "${experiment}" -p species)
     echo -e "LOG: species metadata parsed: \${species}" >> ${repRID}.parseMetadata.log
 
-    # gave design file
-    echo -e "\${endsMeta},\${endsManual},\${stranded},\${spike},\${species},\${exp},\${study}" > design.csv
+    # get read length metadata
+    readLength=\$(python3 ${script_parseMeta} -r ${repRID} -m "${experimentSettings}" -p readLength)
+    if [ "\${readLength}" = "nan"]
+    then
+      readLength="NA"
+    fi
+    echo -e "LOG: read length metadata parsed: \${readLength}" >> ${repRID}.parseMetadata.log
+
+    # save design file
+    echo -e "\${endsMeta},\${endsManual},\${stranded},\${spike},\${species},\${readLength},\${exp},\${study}" > design.csv
     """
 }
 
@@ -248,6 +257,7 @@ endsManual = Channel.create()
 strandedMeta = Channel.create()
 spikeMeta = Channel.create()
 speciesMeta = Channel.create()
+readLengthMeta = Channel.create()
 expRID = Channel.create()
 studyRID = Channel.create()
 metadata.splitCsv(sep: ",", header: false).separate(
@@ -256,6 +266,7 @@ metadata.splitCsv(sep: ",", header: false).separate(
   strandedMeta,
   spikeMeta,
   speciesMeta,
+  readLengthMeta,
   expRID,
   studyRID
 )
@@ -281,25 +292,38 @@ process trimData {
   output:
     path ("*.fq.gz") into fastqsTrim
     path ("*_trimming_report.txt") into trimQC
+    path ("readLength.csv") into inferMetadata_readLength
 
   script:
     """
     hostname > ${repRID}.trimData.log
     ulimit -a >> ${repRID}.trimData.log
 
-    # trim fastq's using trim_galore
+    # trim fastq's using trim_galore and extract median read length
     echo -e "LOG: trimming ${ends}" >> ${repRID}.trimData.log
     if [ "${ends}" == "se" ]
     then
       trim_galore --gzip -q 25 --illumina --length 35 --basename ${repRID} -j `nproc` ${fastq[0]}
+      readLength=\$(zcat *_trimmed.fq.gz | awk '{if(NR%4==2) print length(\$1)}' | sort -n | awk '{a[NR]=\$0}END{print(NR%2==1)?a[int(NR/2)+1]:(a[NR/2]+a[NR/2+1])/2}')
     elif [ "${ends}" == "pe" ]
     then
       trim_galore --gzip -q 25 --illumina --length 35 --paired --basename ${repRID} -j `nproc` ${fastq[0]} ${fastq[1]}
+      readLength=\$(zcat *_1.fq.gz | awk '{if(NR%4==2) print length(\$1)}' | sort -n | awk '{a[NR]=\$0}END{print(NR%2==1)?a[int(NR/2)+1]:(a[NR/2]+a[NR/2+1])/2}')
     fi
     echo -e "LOG: trimmed" >> ${repRID}.trimData.log
+    echo -e "LOG: average trimmed read length: \${readLength}" >> ${repRID}.trimData.log
+    
+    # save read length file
+    echo -e "\${readLength}" > readLength.csv
     """
 }
 
+// Extract calculated read length metadata into channel
+readLengthInfer = Channel.create()
+inferMetadata_readLength.splitCsv(sep: ",", header: false).separate(
+  readLengthInfer
+)
+
 // Replicate trimmed fastq's
 fastqsTrim.into {
   fastqsTrim_alignData
@@ -605,7 +629,7 @@ process getRef {
     val species from speciesInfer_getRef
 
   output:
-    tuple path ("hisat2", type: 'dir'), path ("bed", type: 'dir'), path ("*.fna"), path ("*.gtf")  into reference
+    tuple path ("hisat2", type: 'dir'), path ("bed", type: 'dir'), path ("*.fna"), path ("*.gtf"), path ("geneID.tsv"), path ("Entrez.tsv")  into reference
  
   script:
     """
@@ -641,12 +665,16 @@ process getRef {
       aws s3 cp "\${references}"/bed ./bed --recursive
       aws s3 cp "\${references}"/genome.fna ./
       aws s3 cp "\${references}"/genome.gtf ./
+      aws s3 cp "\${references}"/geneID.tsv ./
+      aws s3 cp "\${references}"/Entrez.tsv ./
     elif [ ${referenceBase} == "/project/BICF/BICF_Core/shared/gudmap/references" ]
     then
       ln -s "\${references}"/hisat2
       ln -s "\${references}"/bed
       ln -s "\${references}"/genome.fna
       ln -s "\${references}"/genome.gtf
+      ln -s "\${references}"/geneID.tsv
+      ln -s "\${references}"/Entrez.tsv
     fi
     echo -e "LOG: fetched" >> ${repRID}.getRef.log
     """
@@ -810,14 +838,16 @@ process countData {
 
   input:
     path script_calculateTPM
+    path script_convertGeneSymbols
     tuple path (bam), path (bai) from dedupBam_countData
     path ref from reference_countData
     val ends from endsInfer_countData
     val stranded from strandedInfer_countData
 
   output:
-    path ("*.countTable.csv") into counts
+    path ("*.tpmTable.csv") into counts
     path ("*.countData.summary") into countsQC
+    path ("assignedReads.csv") into inferMetadata_assignedReads
 
   script:
     """
@@ -837,7 +867,7 @@ process countData {
     elif [ "${stranded}" == "reverse" ]
     then
       stranding=2
-      echo -e "LOG: strandedness set to forward stranded [2]" >> ${repRID}.countData.log
+      echo -e "LOG: strandedness set to reverse stranded [2]" >> ${repRID}.countData.log
     fi
 
     # run featureCounts
@@ -850,13 +880,26 @@ process countData {
       featureCounts -T `nproc` -a ./genome.gtf -G ./genome.fna -g 'gene_name' -o ${repRID}.countData -s \${stranding} -p -B -R SAM --primary --ignoreDup ${repRID}.sorted.deduped.bam
     fi
     echo -e "LOG: counted" >> ${repRID}.countData.log
+    
+    # extract assigned reads
+    grep -m 1 'Assigned' *.countData.summary | grep -oe '\\([0-9.]*\\)' > assignedReads.csv
 
     # calculate TPM from the resulting countData table
     echo -e "LOG: calculating TPM with R" >> ${repRID}.countData.log
     Rscript calculateTPM.R --count "${repRID}.countData"
+
+    # convert gene symbols to Entrez id's
+    echo -e "LOG: convert gene symbols to Entrez id's" >> ${repRID}.countData.log
+    Rscript convertGeneSymbols.R --repRID "${repRID}"
     """
 }
 
+// Extract number of assigned reads metadata into channel
+assignedReadsInfer = Channel.create()
+inferMetadata_assignedReads.splitCsv(sep: ",", header: false).separate(
+  assignedReadsInfer
+)
+
 /*
  *fastqc: run fastqc on untrimmed fastq's
 */
@@ -868,6 +911,7 @@ process fastqc {
 
   output:
     path ("*_fastqc.zip") into fastqc
+    path ("rawReads.csv") into inferMetadata_rawReads
 
   script:
     """
@@ -876,11 +920,19 @@ process fastqc {
 
     # run fastqc
     echo -e "LOG: running fastq on raw fastqs" >> ${repRID}.fastqc.log
-    #fastqc *.fastq.gz -o .
-    touch test_fastqc.zip
+    fastqc *.fastq.gz -o .
+
+    # count raw reads
+    zcat *.R1.fastq.gz | echo \$((`wc -l`/4)) > rawReads.csv
     """
 }
 
+// Extract number of raw reads metadata into channel
+rawReadsInfer = Channel.create()
+inferMetadata_rawReads.splitCsv(sep: ",", header: false).separate(
+  rawReadsInfer
+)
+
 /*
  *dataQC: calculate transcript integrity numbers (TIN) and bin as well as calculate innerdistance of PE replicates
 */
@@ -895,7 +947,8 @@ process dataQC {
     val ends from endsInfer_dataQC
     
   output:
-    path "${repRID}.tin.hist.tsv" into tin
+    path "${repRID}.tin.hist.tsv" into tinHist
+    path "${repRID}.tin.med.csv" into inferMetadata_tinMed
     path "${repRID}.insertSize.inner_distance_freq.txt" into innerDistance
   
   script:
@@ -928,12 +981,19 @@ process dataQC {
     """
 }
 
+// Extract median TIN metadata into channel
+tinMedInfer = Channel.create()
+inferMetadata_tinMed.splitCsv(sep: ",", header: false).separate(
+  tinMedInfer
+)
+
 /*
  *aggrQC: aggregate QC from processes as well as metadata and run MultiQC
 */
 process aggrQC {
   tag "${repRID}"
-  publishDir "${outDir}/qc", mode: 'copy', pattern: "${repRID}.multiqc.html"
+  publishDir "${outDir}/report", mode: 'copy', pattern: "${repRID}.multiqc.html"
+  publishDir "${outDir}/qc", mode: 'copy', pattern: "${repRID}.multiqc_data.json"
 
   input:
     path multiqcConfig
@@ -944,7 +1004,7 @@ process aggrQC {
     path dedupQC
     path countsQC
     path innerDistance
-    path tin
+    path tinHist
     path alignSampleQCs from alignSampleQC_aggrQC.collect()
     path inferExperiment
     val endsManual from endsManual_aggrQC
@@ -956,11 +1016,17 @@ process aggrQC {
     val strandedI from strandedInfer_aggrQC
     val spikeI from spikeInfer_aggrQC
     val speciesI from speciesInfer_aggrQC
+    val readLengthM from readLengthMeta
+    val readLengthI from readLengthInfer
+    val rawReadsI from rawReadsInfer
+    val assignedReadsI from assignedReadsInfer
+    val tinMedI from tinMedInfer
     val expRID
     val studyRID
 
   output:
     path "${repRID}.multiqc.html" into multiqc
+    path "${repRID}.multiqc_data.json" into multiqcJSON
 
   script:
     """
@@ -974,14 +1040,14 @@ process aggrQC {
 
     # make metadata table
     echo -e "LOG: creating metadata table" >> ${repRID}.aggrQC.log
-    echo -e "Source\tSpecies\tEnds\tStranded\tSpike-in" > metadata.tsv
-    echo -e "Infered\t${speciesI}\t${endsI}\t${strandedI}\t${spikeI}" >> metadata.tsv
-    echo -e "Submitter\t${speciesM}\t${endsM}\t${strandedM}\t${spikeM}" >> metadata.tsv
-    echo -e "Manual\t-\t${endsManual}\t-\t-" >> metadata.tsv
+    echo -e "Source\tSpecies\tEnds\tStranded\tSpike-in\tRaw Reads\tAssigned Reads\tMedian Read Length\tMedian TIN" > metadata.tsv
+    echo -e "Submitter\t${speciesM}\t${endsM}\t${strandedM}\t${spikeM}\t-\t-\t'${readLengthM}'\t-" >> metadata.tsv
+    echo -e "Infered\t${speciesI}\t${endsI}\t${strandedI}\t${spikeI}\t-\t-\t-\t-" >> metadata.tsv
+    echo -e "Measured\t-\t${endsManual}\t-\t-\t'${rawReadsI}'\t'${assignedReadsI}'\t'${readLengthI}'\t'${tinMedI}'" >> metadata.tsv
 
     # remove inner distance report if it is empty (SE repRID)
     echo -e "LOG: removing dummy inner distance file" >> ${repRID}.aggrQC.log
-    if [ wc -l ${innerDistance} | awk '{print\${1}}' -eq 0 ]
+    if [ "${endsM}" == "se" ]
     then
       rm -f ${innerDistance}
     fi
@@ -989,5 +1055,6 @@ process aggrQC {
     # run MultiQC
     echo -e "LOG: running multiqc" >> ${repRID}.aggrQC.log
     multiqc -c ${multiqcConfig} . -n ${repRID}.multiqc.html
+    cp ${repRID}.multiqc_data/multiqc_data.json ${repRID}.multiqc_data.json
     """
-}
+}
\ No newline at end of file

workflow/scripts/convertGeneSymbols.R

+gc()
+library(optparse)
+
+option_list=list(
+  make_option("--repRID",action="store",type='character',help="Replicate RID")
+)
+opt=parse_args(OptionParser(option_list=option_list))
+rm(option_list)
+
+countTable <- read.csv(paste0(opt$repRID,".countData.countTable.csv"), stringsAsFactors=FALSE)
+geneID <- read.delim("geneID.tsv", header=FALSE, stringsAsFactors=FALSE)
+Entrez <- read.delim("Entrez.tsv", header=FALSE, stringsAsFactors=FALSE)
+
+convert <- data.frame(geneID=countTable$Geneid)
+convert <- merge(x=convert,y=geneID[,1:2],by.x="geneID",by.y="V2",all.x=TRUE)
+convert <- merge(x=convert,y=Entrez,by.x="V1",by.y="V1",all.x=TRUE)
+convert[is.na(convert$V2),3] <- ""
+convert <- convert[,-1]
+colnames(convert) <- c("GeneID","EntrezID")
+convert <- unique(convert)
+
+output <- merge(x=convert,y=countTable,by.x="GeneID",by.y="Geneid",all.x=TRUE)
+
+write.table(output,file=paste0(opt$repRID,".tpmTable.csv"),sep=",",row.names=FALSE,quote=FALSE)
\ No newline at end of file

workflow/scripts/parseMeta.py

@@ -102,5 +102,10 @@ def main():
             exit(1)
         print(species)
 
+    # Get read length metadata from 'Experiment Settings.csv'
+    if (args.parameter == "readLength"):
+        readLength = metaFile.Read_Length.unique()
+        print(str(readLength).strip('[]'))
+
 if __name__ == '__main__':
     main()

workflow/scripts/splitStudy.py

+#!/usr/bin/env python3
+
+import argparse
+import pandas as pd
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument('-s', '--studyRID',help="The study RID.",required=True)
+    args = parser.parse_args()
+    return args
+
+def main():
+    args = get_args()
+    studyRID=pd.read_json(args.studyRID+"_studyRID.json")
+    if studyRID["RID"].count() > 0:
+        studyRID["RID"].to_csv(args.studyRID+"_studyRID.csv",header=False,index=False)
+    else:
+        raise Exception("No associated replicates found: %s" %
+            studyRID)
+
+if __name__ == '__main__':
+    main()

workflow/scripts/splitStudy.sh

+#!/bin/bash
+
+# query GUDMAP/RBK for study RID
+echo "curl --location --request GET 'https://www.gudmap.org/ermrest/catalog/2/entity/RNASeq:Replicate/Study_RID="${1}"'" | bash > $1_studyRID.json
+
+# extract replicate RIDs
+module load python/3.6.4-anaconda
+python3 ./workflow/scripts/splitStudy.py -s $1
+
+# run pipeline on replicate RIDs in parallel
+module load nextflow/20.01.0
+module load singularity/3.5.3
+while read repRID; do echo ${repRID}; done < "$1_studyRID.csv" | xargs -P 5 -I {} nextflow run workflow/rna-seq.nf --repRID {}
+
+# cleanup study RID files
+rm $1_studyRID.json
+rm $1_studyRID.csv

workflow/scripts/tinHist.py

@@ -15,6 +15,7 @@ def get_args():
 def main():
     args = get_args()
     tin = pd.read_csv(args.repRID + '.sorted.deduped.tin.xls',sep="\t",header=0)
+    
     hist = pd.cut(tin['TIN'],bins=pd.interval_range(start=0,freq=10,end=100,closed='right')).value_counts(sort=False)
     labels = ["{0} - {1}".format(i, i + 9) for i in range(1, 100, 10)]
     #labels[0] = '0 - 10'
@@ -34,6 +35,9 @@ def main():
     hist = hist.T.fillna(0.0).astype(int)
     #hist = hist.apply(lambda x: x/x.sum()*100, axis=1)
     hist.to_csv(args.repRID + '.tin.hist.tsv',sep='\t')
+    medFile = open(args.repRID + '.tin.med.csv',"w")
+    medFile.write(str(round(tin['TIN'][(tin['TIN']!=0)].median(),2)))
+    medFile.close()
 
 if __name__ == '__main__':
-    main()
\ No newline at end of file
+    main()

workflow/tests/test_consistency.py

@@ -24,7 +24,7 @@ def readAssigned(fileAssigned,fileExpectAssigned):
     expect = open(fileExpectAssigned, "r")
     lineAssigned = assigned.readline()
     lineExpect = expect.readline()
-    if lineAssigned.strip() == lineExpect.strip():
+    if int(lineAssigned.strip()) < (int(lineExpect.strip())+(int(lineExpect.strip())*0.00001)) and int(lineAssigned.strip()) > (int(lineExpect.strip())-(int(lineExpect.strip())*0.00001)):
         data = True
 
     return data

workflow/tests/test_parseMetadata.py

@@ -17,7 +17,7 @@ def readLine(fileName):
     data = False
     file = open(fileName, "r")
     line = file.readline()
-    if line.strip() == "uk,se,unstranded,no,Homo sapiens,Experiment_RID,Study_RID,Replicate_RID":
+    if line.strip() == "uk,se,unstranded,no,Homo sapiens,75,Experiment_RID,Study_RID,Replicate_RID":
         data = True
 
     return data