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ADD: process files for transcriptome quant. - several issues, e.g., m…
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pebert committed Dec 30, 2016
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146 changes: 146 additions & 0 deletions docs/quantification/transcriptome/EXPv1.xml
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<?xml version="1.0"?>
<?xml-stylesheet type="text/css" href="http://deep.mpi-inf.mpg.de/DAC/files/style/deep_process_style.css"?>
<process>
<name>EXP</name>
<version>1</version>
<author>
<name>Matthias Barann</name>
<email>m.barann@ikmb.uni-kiel.de</email>
</author>
<description>
* bam2wig.py: Conversion of BAM file to BigWig coverage tracks. One track per strand will be generated.
* htseq-count: Generates read counts on the gene level.
* cufflinks: Generates FPKM values for genes and transcript isoforms.
</description>
<inputs>
<filetype>
<identifier>.bam</identifier>
<format></format>
<quantity>single</quantity>
<comment>Unfiltered aligned reads</comment>
</filetype>
<filetype>
<identifier>.bai</identifier>
<format></format>
<quantity>single</quantity>
<comment>Index file to bam file</comment>
</filetype>
</inputs>
<references>
<filetype>
<identifier>chromInfo.txt</identifier>
<format>text file</format>
<quantity>single</quantity>
<comment>Tab delimited file containing the name and length of the reference sequences: [name][tab][length].</comment>
</filetype>
<filetype>
<identifier>gencode.v19.annotation.gtf</identifier>
<format>GTF</format>
<quantity>single</quantity>
<comment>Gencode gene annotation file in gene transfer format.</comment>
</filetype>
<filetype>
<identifier>reference.fa</identifier>
<format>multi fasta</format>
<quantity>single</quantity>
<comment>The reference genome file; see aspera.dkfz.de > download > results > references > genomes > human > WholeGenome</comment>
</filetype>
</references>
<outputs>
<filetype>
<identifier>[sampleID].EXPv1.[DATE].bamcov.Forward.wig</identifier>
<format>wiggle</format>
<quantity>single</quantity>
<comment>Forward strand wiggle file. Usually it is not necessary to keep this file.</comment>
</filetype>
<filetype>
<identifier>[sampleID].EXPv1.[DATE].bamcov.Reverse.wig</identifier>
<format>wiggle</format>
<quantity>single</quantity>
<comment>Reverse strand wiggle file Usually it is not necessary to keep this file.</comment>
</filetype>
<filetype>
<identifier>[sampleID].EXPv1.[DATE].bamcov.Forward.bw</identifier>
<format>BigWig</format>
<quantity>single</quantity>
<comment>Forward strand BigWig file. This file will only be generated if the UCSC program bamToBigWig can be found in $PATH.</comment>
</filetype>
<filetype>
<identifier>[sampleID].EXPv1.[DATE].bamcov.Reverse.bw</identifier>
<format>BigWig</format>
<quantity>single</quantity>
<comment>Reverse strand BigWig file. This file will only be generated if the UCSC program bamToBigWig can be found in $PATH.</comment>
</filetype>
<filetype>
<identifier>[sampleID].EXPv1.[DATE].readcounts.txt</identifier>
<format>text file</format>
<quantity>single</quantity>
<comment>This file contains the read counts on the gene level.</comment>
</filetype>
<filetype>
<identifier>[sampleID].EXPv1.[DATE].genes.fpkm.tracking</identifier>
<format>text file</format>
<quantity>single</quantity>
<comment>Output file containing the FPKM counts on the gene level.</comment>
</filetype>
<filetype>
<identifier>[sampleID].EXPv1.[DATE].isoforms.fpkm.tracking</identifier>
<format>text file</format>
<quantity>single</quantity>
<comment>Output file containing the FPKM counts on the isoform level.</comment>
</filetype>
<filetype>
<identifier>[sampleID].EXPv1.[DATE].transcripts.gtf</identifier>
<format>gene transfer format</format>
<quantity>single</quantity>
<comment>This file contains assembled transcripts.</comment>
</filetype>
</outputs>
<software>
<tool>
<name>Python</name>
<version>2.7</version>
<command_line><![CDATA[ CMDLINE ]]></command_line>
<loop>no looping</loop>
<comment></comment>
</tool>
<tool>
<name>Samtools</name>
<version>0.1.19-44428cd</version>
<command_line><![CDATA[ CMDLINE ]]></command_line>
<loop>no looping</loop>
<comment></comment>
</tool>
<tool>
<name>bam2wig.py</name>
<version>2.3.9</version>
<command_line><![CDATA[ python bam2wig.py -i ${sample}.bam -s ChromInfo.txt -o ${_sample} -d "1+-,1-+,2++,2--" ]]></command_line>
<loop>no looping</loop>
<comment>The python script is part of the RSeQC software. It will convert a bam file into two wig files (one for each strand). \
If the UCSC program wigToBigWig can be located by the python script, the generated wig files will automatically be converted to bigWig. \
Please note that for some samples the wigToBigWig command might exit with errors. In this case, manually invoking the wigToBigWig \
command on the generated wig files can solve the problem: \
wigToBigWig ${_sample}_Forward.wig -s ChromInfo.txt > ${_sample}_Forward.bw</comment>
</tool>
<tool>
<name>htseq-count</name>
<version>0.5.4p3</version>
<command_line><![CDATA[ samtools sort -n -@ 8 -m 4G ${_sample}.bam ${_sample}_sorted
samtools/samtools view -F 256 ${_sample}_sorted.bam > ${_sample}.sam
htseq-count -s reverse -m intersection-strict -a 20 ${_sample}.sam gencode.v19.annotation.gtf > ${_sample}_htseq.txt ]]>
</command_line>
<loop>no looping</loop>
<comment>DESeq requires bam files sorted by read name (step 1). After sorting, all non-primary alignments are removed during the bam to sam conversion. \
Invoking htseq-count counts the number of reads per gene. Using the mode 'intersection-strict' results in a rather conservative read count. \
Please see http://www-huber.embl.de/users/anders/HTSeq/doc/count.html#count for further information.</comment>
</tool>
<tool>
<name>cufflinks</name>
<version>v2.0.2</version>
<command_line><![CDATA[ cufflinks -p 8 --frag-bias-correct reference.fa --multi-read-correct --library-type fr-firststrand --compatible-hits-norm -G gencode.v19.annotation_transcripts_only.gtf ${_sample}.bam ]]>
</command_line>
<loop>no looping</loop>
<comment>Please see http://cufflinks.cbcb.umd.edu/manual.html for further information.</comment>
</tool>
</software>
</process>
135 changes: 135 additions & 0 deletions docs/quantification/transcriptome/LXPv1.xml
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<?xml version="1.0"?>
<process>
<name>LXP</name>
<version>1</version>
<author>
<name>Anupam Sinha</name>
<email>a.sinha@ikmb.uni-kiel.de</email>
</author>
<!-- Precise description of what this process does, what output is generated and what statistics are computed -->
<description>
* htseq-count: Generates read counts on the gene level.
* cufflinks: Generates FPKM values for genes and transcript isoforms.
* StringTie: Generates FPKM values for genes and transcript isoforms. Also generates .ctab files for analysis using Ballgown.
</description>
<!-- Following section: list input files [samples to be analysed and similar] -->
<inputs>
<filetype>
<identifier>.bam</identifier>
<format></format>
<quantity>single</quantity>
<comment>Unfiltered aligned reads</comment>
</filetype>
</inputs>
<!-- Following section: list reference files [e.g. reference genomes] used in this process -->
<references>
<filetype>
<identifier>gencode.v19.annotation.gtf</identifier>
<format>GTF</format>
<quantity>single</quantity>
<comment>Gencode gene annotation file in gene transfer format.</comment>
</filetype>
<filetype>
<identifier>reference.fa</identifier>
<format>multi fasta</format>
<quantity>single</quantity>
<comment>The reference genome file; see aspera.dkfz.de > download > results > references > genomes > human > WholeGenome</comment>
</filetype>
</references>
<!-- Following section: list output files of process [e.g. fpkm files, read counts files from htseq etc.] -->
<outputs>
<filetype>
<identifier>[sampleID].LXPv1.[DATE].readcounts.txt</identifier>
<format>text file</format>
<quantity>single</quantity>
<comment>This file contains the read counts on the gene level.</comment>
</filetype>
<filetype>
<identifier>[sampleID].LXPv1.[DATE].genes.fpkm.tracking</identifier>
<format>text file</format>
<quantity>single</quantity>
<comment>Output file containing the FPKM counts on the gene level.</comment>
</filetype>
<filetype>
<identifier>[sampleID].LXPv1.[DATE].isoforms.fpkm.tracking</identifier>
<format>text file</format>
<quantity>single</quantity>
<comment>Output file containing the FPKM counts on the isoform level.</comment>
</filetype>
<filetype>
<identifier>[sampleID].LXPv1.[DATE].transcripts.gtf</identifier>
<format>gene transfer format</format>
<quantity>single</quantity>
<comment>This file contains assembled transcripts.</comment>
</filetype>
<filetype>
<identifier>[sampleID].LXPv1.[DATE].stringtie.gtf</identifier>
<format>gene transfer format</format>
<quantity>single</quantity>
<comment>This file contains assembled transcripts.</comment>
</filetype>
<filetype>
<identifier>[sampleID].LXPv1.[DATE].ballgown</identifier>
<format>tab separated fields (.ctab) format</format>
<quantity>five</quantity>
<comment>This is a folder containing 5 .ctab files. These .ctab files contain the expression values of exons, introns and transcripts. Two files list the internal(generated by ballgown) association ids between exons, introns, and transcripts.</comment>
</filetype>
</outputs>

<software>
<tool>
<name>Python</name>
<version>2.7</version>
<command_line><![CDATA[ CMDLINE ]]></command_line>
<loop>no looping</loop>
<comment></comment>
</tool>
<tool>
<name>Samtools</name>
<version>0.1.19-44428cd</version>
<command_line><![CDATA[ CMDLINE ]]></command_line>
<loop>no looping</loop>
<comment></comment>
</tool>
<tool>
<name>htseq-count</name>
<version>0.6.1p1</version>
<command_line>samtools sort -n -@ 8 -m 4G ${_sample}.bam ${_sample}_sorted
samtools/samtools view -F 256 ${_sample}_sorted.bam > ${_sample}.sam
htseq-count -s reverse -m union -a 20 ${_sample}.sam gencode.v19.annotation.gtf > ${_sample}_htseq.txt
</command_line>
<loop>no looping</loop>
<comment>DESeq2 requires bam files sorted by read name (step 1). After sorting, all non-primary alignments are removed during the bam to sam conversion. \
Invoking htseq-count counts the number of reads per gene. \
Please see http://www-huber.embl.de/users/anders/HTSeq/doc/count.html#count for further information.
</comment>
</tool>
<tool>
<name>cufflinks</name>
<version>v2.0.2</version>
<command_line>
<![CDATA[
cufflinks -p 16 --frag-bias-correct reference.fa --multi-read-correct --library-type fr-firststrand
--compatible-hits-norm -G gencode.v19.annotation_transcripts_only.gtf ${_sample}.bam
]]>
</command_line>
<loop>no looping</loop>
<comment>Please see http://cufflinks.cbcb.umd.edu/manual.html for further information.</comment>
</tool>
<tool>
<name>StringTie</name>
<version>v1.0.3</version>
<command_line>
<![CDATA[
stringtie -p 16 -e -b ${_sample}.ballgown -o ${_sample}_stringtie.gtf -G gencode.v19.annotation_transcripts_only.gtf
]]>
</command_line>
<loop>no looping</loop>
<comment>Please see http://ccb.jhu.edu/software/stringtie/ for further information. \
"-b" option creates a folder which contains the .ctab files for analysis using Ballgown. \
Please see https://github.com/alyssafrazee/ballgown for further information.
</comment>
</tool>

</software>
</process>
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