Metadata output update

Cumulative update focused on metadata output:

• Add read length: both submitter entered and inferred (median length)
• Add calculated read counts: both raw and assigned
• Add median TIN
• Output multiqc json (for future use)
• Convert gene symbols to Entrez ID: for data-hub convenience (use version specific metadata - added to references)
• Create bash script to initiate parallel replicate runs from study RID
• Change consistence tests for assigned reads exact match to being within +/- 1/100,000 of expected

PR checklist

• This comment contains a description of changes (with reason)
• If you've fixed a bug or added code that should be tested, add tests!
• Documentation in docs is updated
• Replace dag.png with the most recent CI pipleine integrated_pe artifact
• CHANGELOG.md is updated
• README.md is updated
• LICENSE.md is updated with new contributors
• Docker images moved to production release and changed in pipeline
• Docker images used in the CI unit tests match those used in pipeline

• Close issue
  Closes #52 (closed) Closes #56 (closed)

/cc @ghenry @venkat.malladi

workflow/rna-seq.nf

@@ -299,11 +299,11 @@ process trimData {
     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]=$0}END{print(NR%2==1)?a[int(NR/2)+1]:(a[NR/2]+a[NR/2+1])/2}')
+      readLength=\$(zcat *_trimmed.fq.gz | awk '{if(NR%4==2) print length(\${1})}' | sort -n | awk '{a[NR]=\$0}END{print(NR%2==1)?a[int(NR/2)+1]:(a[NR/2]+a[NR/2+1])/2}')
     elif [ "${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}')
+      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
@@ -317,7 +317,7 @@ process trimData {
 readLengthInfer = Channel.create()
 inferMetadata_readLength.splitCsv(sep: ",", header: false).separate(
   readLengthInfer
-}
+)
 
 
 // Replicate trimmed fastq's