Mercurial > repos > fubar > differential_count_models
diff rgedgeRpaired_nocamera.xml @ 143:1435811cbf01 draft
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| author | iuc |
|---|---|
| date | Thu, 26 Feb 2015 22:41:57 -0500 |
| parents | e7894f37320a |
| children |
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--- a/rgedgeRpaired_nocamera.xml Wed Feb 18 11:37:14 2015 -0500 +++ b/rgedgeRpaired_nocamera.xml Thu Feb 26 22:41:57 2015 -0500 @@ -1,144 +1,124 @@ +<?xml version="1.0"?> <tool id="rgdifferentialcount" name="Differential_Count" version="0.28"> <description>models using BioConductor packages</description> <requirements> - <requirement type="package" version="3.1.2">R</requirement> - <requirement type="package" version="1.3.18">graphicsmagick</requirement> - <requirement type="package" version="9.10">ghostscript</requirement> - <requirement type="package" version="2.14">biocbasics</requirement> + <requirement type="package" version="3.1.2">R</requirement> + <requirement type="package" version="1.3.18">graphicsmagick</requirement> + <requirement type="package" version="9.10">ghostscript</requirement> + <requirement type="package" version="2.14">biocbasics</requirement> </requirements> - <command interpreter="python"> rgToolFactory.py --script_path "$runme" --interpreter "Rscript" --tool_name "Differential_Counts" --output_dir "$html_file.files_path" --output_html "$html_file" --make_HTML "yes" </command> <inputs> - <param name="input1" type="data" format="tabular" label="Select an input matrix - rows are contigs, columns are counts for each sample" - help="Use the HTSeq based count matrix preparation tool to create these matrices from BAM/SAM files and a GTF file of genomic features"/> - <param name="title" type="text" value="Differential Counts" size="80" label="Title for job outputs" - help="Supply a meaningful name here to remind you what the outputs contain"> + <param name="input1" type="data" format="tabular" label="Select an input matrix - rows are contigs, columns are counts for each sample" help="Use the HTSeq based count matrix preparation tool to create these matrices from BAM/SAM files and a GTF file of genomic features"/> + <param name="title" type="text" value="Differential Counts" size="80" label="Title for job outputs" help="Supply a meaningful name here to remind you what the outputs contain"> <sanitizer invalid_char=""> - <valid initial="string.letters,string.digits"><add value="_" /> </valid> + <valid initial="string.letters,string.digits"> + <add value="_"/> + </valid> </sanitizer> </param> <param name="treatment_name" type="text" value="Treatment" size="50" label="Treatment Name"/> - <param name="Treat_cols" label="Select columns containing treatment." type="data_column" data_ref="input1" numerical="True" - multiple="true" use_header_names="true" size="120" display="checkboxes" force_select="True"> - <validator type="no_options" message="Please select at least one column."/> + <param name="Treat_cols" label="Select columns containing treatment." type="data_column" data_ref="input1" numerical="True" multiple="true" use_header_names="true" size="120" display="checkboxes" force_select="True"> + <validator type="no_options" message="Please select at least one column."/> </param> <param name="control_name" type="text" value="Control" size="50" label="Control Name"/> - <param name="Control_cols" label="Select columns containing control." type="data_column" data_ref="input1" numerical="True" - multiple="true" use_header_names="true" size="120" display="checkboxes" force_select="True"> + <param name="Control_cols" label="Select columns containing control." type="data_column" data_ref="input1" numerical="True" multiple="true" use_header_names="true" size="120" display="checkboxes" force_select="True"> </param> - <param name="subjectids" type="text" optional="true" size="120" value = "" - label="IF SUBJECTS NOT ALL INDEPENDENT! Enter comma separated strings to indicate sample labels for (eg) pairing - must be one for every column in input" - help="Leave blank if no pairing, but eg if data from sample id A99 is in columns 2,4 and id C21 is in 3,5 then enter 'A99,C21,A99,C21'"> + <param name="subjectids" type="text" optional="true" size="120" value="" label="IF SUBJECTS NOT ALL INDEPENDENT! Enter comma separated strings to indicate sample labels for (eg) pairing - must be one for every column in input" help="Leave blank if no pairing, but eg if data from sample id A99 is in columns 2,4 and id C21 is in 3,5 then enter 'A99,C21,A99,C21'"> <sanitizer> - <valid initial="string.letters,string.digits"><add value="," /> </valid> + <valid initial="string.letters,string.digits"> + <add value=","/> + </valid> </sanitizer> </param> - <param name="fQ" type="float" value="0.3" size="5" label="Non-differential contig count quantile threshold - zero to analyze all non-zero read count contigs" - help="May be a good or a bad idea depending on the biology and the question. EG 0.3 = sparsest 30% of contigs with at least one read are removed before analysis"/> - <param name="useNDF" type="boolean" truevalue="T" falsevalue="F" checked="false" size="1" - label="Non differential filter - remove contigs below a threshold (1 per million) for half or more samples" - help="May be a good or a bad idea depending on the biology and the question. This was the old default. Quantile based is available as an alternative"/> - + <param name="fQ" type="float" value="0.3" size="5" label="Non-differential contig count quantile threshold - zero to analyze all non-zero read count contigs" help="May be a good or a bad idea depending on the biology and the question. EG 0.3 = sparsest 30% of contigs with at least one read are removed before analysis"/> + <param name="useNDF" type="boolean" truevalue="T" falsevalue="F" checked="false" size="1" label="Non differential filter - remove contigs below a threshold (1 per million) for half or more samples" help="May be a good or a bad idea depending on the biology and the question. This was the old default. Quantile based is available as an alternative"/> <conditional name="edgeR"> - <param name="doedgeR" type="select" - label="Run this model using edgeR" - help="edgeR uses a negative binomial model and seems to be powerful, even with few replicates"> - <option value="F">Do not run edgeR</option> - <option value="T" selected="true">Run edgeR</option> - </param> - <when value="T"> - <param name="edgeR_priordf" type="integer" value="10" size="3" - label="prior.df for tagwise dispersion - larger value = more squeezing of tag dispersions to common dispersion. Replaces prior.n and prior.df = prior.n * residual.df" - help="10 = edgeR default. Use a larger value to 'smooth' small samples. See edgeR docs and note below"/> - <param name="edgeR_robust_method" type="select" value="20" size="3" - label="Use robust dispersion method" - help="Use ordinary, anscombe or deviance robust deviance estimates"> - <option value="ordinary" selected="true">Use ordinary deviance estimates</option> - <option value="deviance">Use robust deviance estimates</option> - <option value="anscombe">use Anscombe robust deviance estimates</option> - </param> - </when> - <when value="F"></when> + <param name="doedgeR" type="select" label="Run this model using edgeR" help="edgeR uses a negative binomial model and seems to be powerful, even with few replicates"> + <option value="F">Do not run edgeR</option> + <option value="T" selected="true">Run edgeR</option> + </param> + <when value="T"> + <param name="edgeR_priordf" type="integer" value="10" size="3" label="prior.df for tagwise dispersion - larger value = more squeezing of tag dispersions to common dispersion. Replaces prior.n and prior.df = prior.n * residual.df" help="10 = edgeR default. Use a larger value to 'smooth' small samples. See edgeR docs and note below"/> + <param name="edgeR_robust_method" type="select" value="20" size="3" label="Use robust dispersion method" help="Use ordinary, anscombe or deviance robust deviance estimates"> + <option value="ordinary" selected="true">Use ordinary deviance estimates</option> + <option value="deviance">Use robust deviance estimates</option> + <option value="anscombe">use Anscombe robust deviance estimates</option> + </param> + </when> + <when value="F"/> </conditional> <conditional name="DESeq2"> - <param name="doDESeq2" type="select" - label="Run the same model with DESeq2 and compare findings" - help="DESeq2 is an update to the DESeq package. It uses different assumptions and methods to edgeR"> - <option value="F" selected="true">Do not run DESeq2</option> - <option value="T">Run DESeq2</option> - </param> - <when value="T"> - <param name="DESeq_fitType" type="select"> - <option value="parametric" selected="true">Parametric (default) fit for dispersions</option> - <option value="local">Local fit - this will automagically be used if parametric fit fails</option> - <option value="mean">Mean dispersion fit- use this if you really understand what you're doing - read the fine manual linked below in the documentation</option> - </param> - </when> - <when value="F"> </when> + <param name="doDESeq2" type="select" label="Run the same model with DESeq2 and compare findings" help="DESeq2 is an update to the DESeq package. It uses different assumptions and methods to edgeR"> + <option value="F" selected="true">Do not run DESeq2</option> + <option value="T">Run DESeq2</option> + </param> + <when value="T"> + <param name="DESeq_fitType" type="select"> + <option value="parametric" selected="true">Parametric (default) fit for dispersions</option> + <option value="local">Local fit - this will automagically be used if parametric fit fails</option> + <option value="mean">Mean dispersion fit- use this if you really understand what you're doing - read the fine manual linked below in the documentation</option> + </param> + </when> + <when value="F"> </when> </conditional> - <param name="doVoom" type="select" - label="Run the same model with Voom/limma and compare findings" - help="Voom uses counts per million and a precise transformation of variance so count data can be analysed using limma"> + <param name="doVoom" type="select" label="Run the same model with Voom/limma and compare findings" help="Voom uses counts per million and a precise transformation of variance so count data can be analysed using limma"> <option value="F" selected="true">Do not run VOOM</option> <option value="T">Run VOOM</option> - </param> - <param name="fdrthresh" type="float" value="0.05" size="5" label="P value threshold for FDR filtering for amily wise error rate control" - help="Conventional default value of 0.05 recommended"/> - <param name="fdrtype" type="select" label="FDR (Type II error) control method" - help="Use fdr or bh typically to control for the number of tests in a reliable way"> - <option value="fdr" selected="true">fdr</option> - <option value="BH">Benjamini Hochberg</option> - <option value="BY">Benjamini Yukateli</option> - <option value="bonferroni">Bonferroni</option> - <option value="hochberg">Hochberg</option> - <option value="holm">Holm</option> - <option value="hommel">Hommel</option> - <option value="none">no control for multiple tests</option> + </param> + <param name="fdrthresh" type="float" value="0.05" size="5" label="P value threshold for FDR filtering for amily wise error rate control" help="Conventional default value of 0.05 recommended"/> + <param name="fdrtype" type="select" label="FDR (Type II error) control method" help="Use fdr or bh typically to control for the number of tests in a reliable way"> + <option value="fdr" selected="true">fdr</option> + <option value="BH">Benjamini Hochberg</option> + <option value="BY">Benjamini Yukateli</option> + <option value="bonferroni">Bonferroni</option> + <option value="hochberg">Hochberg</option> + <option value="holm">Holm</option> + <option value="hommel">Hommel</option> + <option value="none">no control for multiple tests</option> </param> </inputs> <outputs> <data format="tabular" name="out_edgeR" label="${title}_topTable_edgeR.xls"> - <filter>edgeR['doedgeR'] == "T"</filter> + <filter>edgeR['doedgeR'] == "T"</filter> </data> <data format="tabular" name="out_DESeq2" label="${title}_topTable_DESeq2.xls"> - <filter>DESeq2['doDESeq2'] == "T"</filter> + <filter>DESeq2['doDESeq2'] == "T"</filter> </data> <data format="tabular" name="out_VOOM" label="${title}_topTable_VOOM.xls"> - <filter>doVoom == "T"</filter> + <filter>doVoom == "T"</filter> </data> <data format="html" name="html_file" label="${title}.html"/> </outputs> - <stdio> - <exit_code range="4" level="fatal" description="Number of subject ids must match total number of samples in the input matrix" /> - </stdio> - <tests> -<test> -<param name='input1' value='test_bams2mx.xls' ftype='tabular' /> - <param name='treatment_name' value='liver' /> - <param name='title' value='edgeRtest' /> - <param name='useNDF' value='' /> - <param name='doedgeR' value='T' /> - <param name='doVoom' value='T' /> - <param name='doDESeq2' value='T' /> - <param name='fdrtype' value='fdr' /> - <param name='edgeR_priordf' value="8" /> - <param name='edgeR_robust' value="ordinary" /> - <param name='fdrthresh' value="0.05" /> - <param name='control_name' value='heart' /> - <param name='subjectids' value='' /> - <param name='Control_cols' value='3,4,5,9' /> - <param name='Treat_cols' value='2,6,7,8' /> - <output name='out_edgeR' file='edgeRtest1out.xls' compare='diff' lines_diff='20' /> - <output name='html_file' file='edgeRtest1out.html' compare='diff' lines_diff='20' /> -</test> -</tests> - -<configfiles> -<configfile name="runme"> -<![CDATA[ + <stdio> + <exit_code range="4" level="fatal" description="Number of subject ids must match total number of samples in the input matrix"/> + </stdio> + <tests> + <test> + <param name="input1" value="test_bams2mx.xls" ftype="tabular"/> + <param name="treatment_name" value="liver"/> + <param name="title" value="edgeRtest"/> + <param name="useNDF" value=""/> + <param name="doedgeR" value="T"/> + <param name="doVoom" value="T"/> + <param name="doDESeq2" value="T"/> + <param name="fdrtype" value="fdr"/> + <param name="edgeR_priordf" value="8"/> + <param name="edgeR_robust" value="ordinary"/> + <param name="fdrthresh" value="0.05"/> + <param name="control_name" value="heart"/> + <param name="subjectids" value=""/> + <param name="Control_cols" value="3,4,5,9"/> + <param name="Treat_cols" value="2,6,7,8"/> + <output name="out_edgeR" file="edgeRtest1out.xls" compare="diff" lines_diff="20"/> + <output name="html_file" file="edgeRtest1out.html" compare="diff" lines_diff="20"/> + </test> + </tests> + <configfiles> + <configfile name="runme"><![CDATA[ # # edgeR.Rscript # updated feb 2014 adding outlier-robust deviance estimate options by ross for R 3.0.2/bioc 2.13 @@ -885,8 +865,8 @@ sink() ]]> </configfile> -</configfiles> -<help> + </configfiles> + <help> **What it does** @@ -1063,10 +1043,7 @@ .. _limma_VOOM: http://www.bioconductor.org/packages/release/bioc/html/limma.html .. _Galaxy: http://getgalaxy.org </help> -<citations> + <citations> <citation type="doi">doi: 10.1093/bioinformatics/btp616</citation> -</citations> - + </citations> </tool> - -