Mercurial > repos > bgruening > deseq2
changeset 29:07620fe97c88 draft default tip
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/deseq2 commit d033f887f37ec95f83a8786e8463e0c744773cc4
| author | bgruening |
|---|---|
| date | Sat, 10 Dec 2016 18:33:07 -0500 |
| parents | 6947d8ed51cc |
| children | |
| files | deseq2.R deseq2.xml helper.py readme.md test-data/GSM461176_untreat_single.counts test-data/GSM461177_untreat_paired.counts test-data/GSM461178_untreat_paired.counts test-data/GSM461179_treat_single.counts test-data/GSM461180_treat_paired.counts test-data/GSM461181_treat_paired.counts test-data/GSM461182_untreat_single.counts test-data/deseq2_out.tab test-data/deseq2_out_filtered.tab tool_dependencies.xml |
| diffstat | 14 files changed, 5 insertions(+), 148987 deletions(-) [+] |
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--- a/deseq2.R Wed Dec 03 14:23:27 2014 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,144 +0,0 @@ -## Setup R error handling to go to stderr -options( show.error.messages=F, error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } ) -# we need that to not crash galaxy with an UTF8 error on German LC settings. -Sys.setlocale("LC_MESSAGES", "en_US.UTF-8") - -library('getopt') -library('rjson') -library('DESeq2') -library("RColorBrewer") -library("gplots") - -options(stringAsfactors = FALSE, useFancyQuotes = FALSE) -args <- commandArgs(trailingOnly = TRUE) - -#get options, using the spec as defined by the enclosed list. -#we read the options from the default: commandArgs(TRUE). -spec = matrix(c( - 'verbose', 'v', 2, "integer", - 'help' , 'h', 0, "logical", - 'outfile' , 'o', 1, "character", - 'outfilefiltered' , 'f', 1, "character", - 'plots' , 'p', 2, "character", - 'factors', 'm', 2, "character", - 'filtermode', 'l', 2, "character", - 'threshold', 'c', 2, "double", - 'organism', 'g', 2, "character" -), byrow=TRUE, ncol=4); -opt = getopt(spec); - - -# if help was asked for print a friendly message -# and exit with a non-zero error code -if ( !is.null(opt$help) ) { - cat(getopt(spec, usage=TRUE)); - q(status=1); -} - -if( is.null(opt$filtermode)) - opt$filtermode = "absolute" - -trim <- function (x) gsub("^\\s+|\\s+$", "", x) -opt$samples <- trim(opt$samples) -opt$factors <- trim(opt$factors) - - -generatePlots <-function(dds, title_prefix){ - plotDispEsts(dds, main= paste(title_prefix, "Dispersion estimate plot")) - plotMA(dds, main= paste(title_prefix, "MA-plot")) - - select <- order(rowMeans(counts(dds,normalized=TRUE)),decreasing=TRUE)[1:30] - hmcol <- colorRampPalette(brewer.pal(9, "GnBu"))(100) - rld <- rlogTransformation(dds, blind=TRUE) - vsd <- varianceStabilizingTransformation(dds, blind=TRUE) - distsRL <- dist(t(assay(rld))) - mat <- as.matrix(distsRL) - heatmap.2(mat, trace="none", col = rev(hmcol), main = paste(title_prefix, "Sample-to-sample distances"), margin=c(13,13)) -} - -parser <- newJSONParser() -parser$addData( opt$factors ) -factorsList <- parser$getObject() - -sampleTable<-data.frame() -factorNames<-c() -primaryfactor = TRUE -for(factor in factorsList){ - factorName<-factor[[1]] - factorNames<-append(factorNames, factorName) - factorValuesMapList<-factor[[2]] - c = length(factorValuesMapList) - for (factorValuesMap in factorValuesMapList){ - for(files in factorValuesMap){ - fvc = 0 - for(file in files){ - fvc = fvc+1 - if(primaryfactor) { - sampleTable[basename(file),"sampleName"]<-paste(fvc,names(factorValuesMap),sep="_") - } - sampleTable[basename(file),"fileName"]<-file - sampleTable[basename(file),factorName]<-paste(c,names(factorValuesMap),sep="_") - } - } - c = c-1 - } - primaryfactor = FALSE -} - -factorNames<-rev(factorNames) -designFormula <- as.formula(paste("", paste(factorNames, collapse=" + "), sep=" ~ ")) - -ddsHTSeq = DESeqDataSetFromHTSeqCount(sampleTable = sampleTable, - directory = "", - design = designFormula) - -ddsHTSeq <- DESeq(ddsHTSeq) -#ddsHTSeq <- nbinomWaldTest(ddsHTSeq, cooksCutoff=FALSE) -deseqRes <- results(ddsHTSeq) -mcols(deseqRes)$description - -resSorted <- deseqRes[order(deseqRes$padj),] -head(resSorted) -write.table(as.data.frame(resSorted), file = opt$outfile, sep="\t", quote = FALSE, append=TRUE, col.names = FALSE) - - -if(opt$filtermode == "absolute"){ - use = (deseqRes$baseMean > opt$threshold & !is.na(deseqRes$pvalue)) -} else if(opt$filtermode == "quantile"){ - opt$threshold = opt$threshold/100 - print(paste("Threshold:", opt$threshold)) - print(quantile(unique(deseqRes$baseMean), probs = opt$threshold)) - use = (deseqRes$baseMean > quantile(unique(deseqRes$baseMean), probs = opt$threshold) & (!is.na(deseqRes$pvalue))) -} else{ - print(paste("Unknown filtermode:", opt$filtermode)) - q("no", 1, FALSE) -} - -ddsHTSeqFilt <- ddsHTSeq[use, ] -ddsHTSeqFilt <- DESeq(ddsHTSeqFilt) -#ddsHTSeqFilt <- nbinomWaldTest(ddsHTSeqFilt, cooksCutoff=FALSE) -deseqResFilt <- results(ddsHTSeqFilt) -mcols(deseqResFilt)$description - -resFiltSorted <- deseqResFilt[order(deseqResFilt$padj),] -head(resFiltSorted) -write.table(as.data.frame(resFiltSorted), file = opt$outfilefiltered, sep="\t", quote = FALSE, append=TRUE, col.names = FALSE) - -if(!is.null(opt$plots)){ - pdf(opt$plots) - generatePlots(ddsHTSeq, "Complete: ") - generatePlots(ddsHTSeqFilt, "Filtered: ") - ## p-value distribution - h1 <- hist(deseqRes$pvalue[!use], breaks=50, plot=FALSE) - h2 <- hist(deseqRes$pvalue[use], breaks=50, plot=FALSE) - colori <- c(`filtered out`="khaki", `complete`="powderblue") - barplot(height = rbind(h1$counts, h2$counts), beside = FALSE, - col = colori, space = 0, main = "Distribution of p-values", ylab="frequency") - text(x = c(0, length(h1$counts)), y = 0, label = paste(c(0,1)), adj = c(0.5,1.7), xpd=NA) - legend("topright", fill=rev(colori), legend=rev(names(colori))) - dev.off() -} - -sessionInfo() - -
--- a/deseq2.xml Wed Dec 03 14:23:27 2014 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,169 +0,0 @@ -<tool id="iuc_deseq2" name="DESeq2" version="2.1.6.0"> - <description>Determines differentially expressed features from count tables</description> - <requirements> - <requirement type="binary">Rscript</requirement> - <requirement type="R-module">DESeq2</requirement> - <!-- odering is crucial, otherwise R will override the ENV variables from deseq2 --> - <requirement type="package" version="3.1.0">R</requirement> - <requirement type="package" version="1.6.1">deseq2</requirement> - </requirements> - <code file="helper.py" /> - <command interpreter="Rscript"> - #import json - deseq2.R - -o "$deseq_out" - --outfilefiltered "$deseq_out_filtered" - - #if $pdf: - -p "$plots" - #end if - - #set $temp_factor_names = list() - #for $factor in $rep_factorName: - - #set $temp_factor = list() - #for $level in $factor.rep_factorLevel: - #set $count_files = list() - #for $file in $level.countsFile: - $count_files.append(str($file)) - #end for - $temp_factor.append( {str($level.factorLevel): $count_files} ) - #end for - $temp_factor_names.append([str($factor.factorName), $temp_factor]) - - #end for - - -m '#echo json.dumps(temp_factor_names)#' - #if str($filtermode.mode) == "absolute": - -c $filtermode.count_abs - #elif str($filtermode.mode) == "quantile": - -c $filtermode.count_quant - #end if - --filtermode $filtermode.mode - </command> - <stdio> - <regex match="Execution halted" - source="both" - level="fatal" - description="Execution halted." /> - <regex match="Error in" - source="both" - level="fatal" - description="An undefined error occured, please check your intput carefully and contact your administrator." /> - </stdio> - <inputs> - <repeat name="rep_factorName" title="Factor" min="1"> - <param name="factorName" type="text" value="FactorName" label="Specify a factor name" - help="Only letters, numbers and underscores will be retained in this field"> - <sanitizer> - <valid initial="string.letters,string.digits"><add value="_" /></valid> - </sanitizer> - </param> - <repeat name="rep_factorLevel" title="Factor level" min="2" max="2" default="2"> - <param name="factorLevel" type="text" value="FactorLevel" label="Specify a factor level" - help="Only letters, numbers and underscores will be retained in this field"> - <sanitizer> - <valid initial="string.letters,string.digits"><add value="_" /></valid> - </sanitizer> - </param> - <param name="countsFile" type="data" multiple="true" label="Counts file"/> - </repeat> - </repeat> - <conditional name="filtermode"> - <param name="mode" type="select" label="Filter out features with following criteria"> - <option value="absolute">Filter based on absolute normalized mean counts</option> - <option value="quantile">Filter based on quantiles</option> - </param> - <when value="absolute"> - <param name="count_abs" size="10" type="float" value="10.0" label="Filter out features with mean normalized counts lower than this value"/> - </when> - <when value="quantile"> - <param name="count_quant" size="10" type="float" value="10.0" min="0" max="100" label="Filter out features with mean normalized counts lower than this % of values" /> - </when> - </conditional> - <param name="pdf" type="boolean" truevalue="yes" falsevalue="no" checked="true" label="Visualising the analysis results" - help="output an additional PDF files" /> - </inputs> - - <outputs> - <data format="tabular" name="deseq_out" label="DESeq2 result file on ${on_string}"/> - <data format="tabular" name="deseq_out_filtered" label="Independent filtering result file on ${on_string}"/> - <data format="pdf" name="plots" label="DESeq2 plots on ${on_string}"> - <filter>pdf == True</filter> - </data> - </outputs> - - <tests> - <test> - <repeat name="rep_factorName"> - <param name="factorName" value="Treatment"/> - <repeat name="rep_factorLevel"> - <param name="factorLevel" value="Treated"/> - <param name="countsFile" value="GSM461179_treat_single.counts,GSM461180_treat_paired.counts,GSM461181_treat_paired.counts"/> - </repeat> - <repeat name="rep_factorLevel"> - <param name="factorLevel" value="Untreated"/> - <param name="countsFile" value="GSM461176_untreat_single.counts,GSM461177_untreat_paired.counts,GSM461178_untreat_paired.counts,GSM461182_untreat_single.counts"/> - </repeat> - </repeat> - <param name="pdf" value="no"/> - <output name="deseq_out" file="deseq2_out.tab"/> - <output name="deseq_out_filtered" file="deseq2_out_filtered.tab"/> - </test> - </tests> - - <help> - -.. class:: infomark - -**What it does** - -Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution - - -**Inputs** - -DESeq2_ takes count tables that generated from the htseq-count as input. Count tables must be generated for each sample individually. DESeq2 is capable of handling multiple factors that effect your experiment. The first factor you input is considered as the primary factor that affects gene expressions. You also input several secondary factors that might influence your experiment. But the final output will be changes in genes due to primary factor in presence of secondary factors. Each factor has two levels/states. You need to select appropriate count table from your history for each factor level. - -The following table gives some examples of factors and their levels: - -========= ============== =============== -Factor Factor level 1 Factor level 2 ---------- -------------- --------------- -Treatment Treated Untreated ---------- -------------- --------------- -Condition Knockdown Wildtype ---------- -------------- --------------- -TimePoint Day4 Day1 ---------- -------------- --------------- -SeqType SingleEnd PairedEnd ---------- -------------- --------------- -Gender Female Male -========= ============== =============== - -*Note*: Output log2 fold changes are based on primary factor level 1 vs. factor level2. Here the order of factor levels is important. For example, for the factor 'Treatment' given in above table, DESeq2 computes fold changes of 'Treated' samples against 'Untreated', i.e. the values correspond to up or down regulations of genes in Treated samples. - -**Output** - -DESeq2_ generates a tabular file containing the different columns and optional visualized results as PDF. - -====== ========================================================== -Column Description ------- ---------------------------------------------------------- - 1 Gene Identifiers - 2 mean normalised counts, averaged over all samples from both conditions - 3 the logarithm (to basis 2) of the fold change (See the note in inputs section) - 4 standard error estimate for the log2 fold change estimate - 5 p value for the statistical significance of this change - 6 p value adjusted for multiple testing with the Benjamini-Hochberg procedure - which controls false discovery rate (FDR) -====== ========================================================== - - -.. _DESeq2: http://master.bioconductor.org/packages/release/bioc/html/DESeq2.html - - </help> - <citations> - <citation type="doi">10.1101/002832</citation> - </citations> -</tool>
--- a/helper.py Wed Dec 03 14:23:27 2014 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,41 +0,0 @@ - -from galaxy.tools.parameters import DataToolParameter - -def validate_input( trans, error_map, param_values, page_param_map ): - """ - Validates the user input, before execution. - """ - factors = param_values['rep_factorName'] - factor_name_list = [] - factor_duplication = False - level_duplication = False - - for factor in factors: - # factor names should be unique - fn = factor['factorName'] - if fn in factor_name_list: - factor_duplication = True - break - factor_name_list.append( fn ) - - level_name_list = list() - factor_index_list = list() - - for level in factor['rep_factorLevel']: - # level names under one factor should be unique - fl = level['factorLevel'] - if fl in level_name_list: - level_duplication = True - level_name_list.append( fl ) - - if level_duplication: - error_map['rep_factorName'] = [ dict() for t in factors ] - for i in range( len( factors ) ): - error_map['rep_factorName'][i]['rep_factorLevel'] = [ {'factorLevel': 'Factor levels for each factor need to be unique'} for t in factor['rep_factorLevel'] ] - break - - if factor_duplication: - error_map['rep_factorName'] = [ dict() for t in factors ] - for i in range( len( factors ) ): - error_map['rep_factorName'][i]['factorName'] = 'Factor names need to be unique.' -
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/readme.md Sat Dec 10 18:33:07 2016 -0500 @@ -0,0 +1,5 @@ +IUC has taken over +================== + +The DESeq2 wrappers are now located under https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2. +Maintenance and development will happen under the IUC umbrella!
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--- a/test-data/GSM461178_untreat_paired.counts Wed Dec 03 14:23:27 2014 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,14874 +0,0 @@ -FBgn0000003 0 -FBgn0000008 57 -FBgn0000014 0 -FBgn0000015 1 -FBgn0000017 2834 -FBgn0000018 273 -FBgn0000022 0 -FBgn0000024 2 -FBgn0000028 0 -FBgn0000032 648 -FBgn0000036 0 -FBgn0000037 0 -FBgn0000038 0 -FBgn0000039 0 -FBgn0000042 50543 -FBgn0000043 17159 -FBgn0000044 14 -FBgn0000045 6 -FBgn0000046 5 -FBgn0000047 3 -FBgn0000052 1808 -FBgn0000053 1386 -FBgn0000054 427 -FBgn0000055 0 -FBgn0000056 0 -FBgn0000057 531 -FBgn0000061 1 -FBgn0000063 233 -FBgn0000064 5205 -FBgn0000071 84 -FBgn0000075 1 -FBgn0000077 156 -FBgn0000078 30 -FBgn0000079 201 -FBgn0000083 4230 -FBgn0000084 1456 -FBgn0000092 10 -FBgn0000094 4 -FBgn0000097 1890 -FBgn0000099 1 -FBgn0000100 21320 -FBgn0000108 32 -FBgn0000109 99 -FBgn0000114 0 -FBgn0000115 403 -FBgn0000116 258 -FBgn0000117 7410 -FBgn0000119 461 -FBgn0000120 0 -FBgn0000121 1 -FBgn0000137 0 -FBgn0000139 546 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--- a/tool_dependencies.xml Wed Dec 03 14:23:27 2014 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,9 +0,0 @@ -<?xml version="1.0"?> -<tool_dependency> - <package name="R" version="3.1.0"> - <repository changeset_revision="a6cc7706ea14" name="package_r_3_1_0" owner="iuc" toolshed="https://testtoolshed.g2.bx.psu.edu" /> - </package> - <package name="deseq2" version="1.6.1"> - <repository changeset_revision="5beee6b62be7" name="package_deseq2_1_6_1" owner="iuc" toolshed="https://testtoolshed.g2.bx.psu.edu" /> - </package> -</tool_dependency>