Mercurial > repos > lecorguille > anova
changeset 8:c2be3b890724 draft
planemo upload commit 00a7f9aadf30a7d728eb4df72ca38ebe5dd7be03
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--- a/Makefile Mon Apr 04 08:46:20 2016 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,23 +0,0 @@ -# USAGE: make [install|clean] - -# -------- VARIABLE -------- - -OBJ=anova.tgz -DEP=abims_anova.r abims_anova.xml static test-data - - -# ------------------------ - -all: $(OBJ) - -$(OBJ): $(DEP) - tar --exclude=".svn" -zchf $@ $^ - -# ------------------------ - -install: $(OBJ) - mv *.tgz ~ - -clean: - rm *.tgz -
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/README.md Tue Jun 06 09:43:23 2017 -0400 @@ -0,0 +1,39 @@ +Anova for Galaxy +================= + +[](http://bioconda.github.io) [](https://travis-ci.org/workflow4metabolomics/anova) + +Our project +----------- +The [Workflow4Metabolomics](http://workflow4metabolomics.org), W4M in short, is a French infrastructure offering software tool processing, analyzing and annotating metabolomics data. It is based on the Galaxy platform. + + +Anova +------ +Analysis of variance (ANOVA) is a collection of statistical models used to analyze the differences among group means and their associated procedures (such as "variation" among and between groups), developed by statistician and evolutionary biologist Ronald Fisher. + +Source: [https://en.wikipedia.org/wiki/Analysis_of_variance](https://en.wikipedia.org/wiki/Analysis_of_variance) + + +Galaxy +------ +Galaxy is an open, web-based platform for data intensive biomedical research. Whether on the free public server or your own instance, you can perform, reproduce, and share complete analyses. + +Homepage: [https://galaxyproject.org/](https://galaxyproject.org/) + + +Conda +----- +[](http://bioconda.github.io) + +[Conda](http://conda.pydata.org/) is package manager that among many other things can be used to manage Python packages. + +Travis +------ +[](https://travis-ci.org/workflow4metabolomics/anova) + +Test and Deploy with Confidence. Easily sync your GitHub projects with Travis CI and you'll be testing your code in minutes! + +Historic contributors +--------------------- + - Gildas Le Corguillé @lecorguille - [ABiMS](http://abims.sb-roscoff.fr/) / [IFB](http://www.france-bioinformatique.fr/) - [UPMC](www.upmc.fr)/[CNRS](www.cnrs.fr) - [Station Biologique de Roscoff](http://www.sb-roscoff.fr/) - France
--- a/README.rst Mon Apr 04 08:46:20 2016 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,21 +0,0 @@ - -Changelog/News --------------- - - -**Version 1.1.4 04/04/2016** - -- TEST: refactoring to pass planemo test using conda dependencies - - -Test Status ------------ - -``` -planemo conda_install . -planemo test --install_galaxy --conda_dependency_resolution . - -#All 1 test(s) executed passed. -#abims_anova[0]: passed -``` -
--- a/abims_anova.r Mon Apr 04 08:46:20 2016 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,132 +0,0 @@ -#!/usr/local/public/bin/Rscript -# version="1.1" - -# date: 06-06-2012 -# update: 18-02-2014 -# **Authors** Gildas Le Corguille ABiMS - UPMC/CNRS - Station Biologique de Roscoff - gildas.lecorguille|at|sb-roscoff.fr - -# abims_anova.r version 20140218 - -library(batch) - - -# function avova -anova = function (file, sampleinfo, mode="column", condition=1, interaction=F, method="BH", threshold=0.01, selection_method="intersection", sep=";", dec=".", outputdatapvalue="anova.data.output", outputdatafiltered="anova.datafiltered.output") { - - - if (sep=="tabulation") sep="\t" - if (sep=="semicolon") sep=";" - if (sep=="comma") sep="," - - anova_formula_operator = "+" - if (interaction) anova_formula_operator = "*" - - # -- import -- - data=read.table(file, header = TRUE, row.names=1, sep = sep, quote="\"", dec = dec, fill = TRUE, comment.char="",na.strings = "NA") - - if (mode == "row") data=t(data) - - sampleinfoTab=read.table(sampleinfo, header = TRUE, row.names=1, sep = sep, quote="\"") - rownames(sampleinfoTab) = make.names(rownames(sampleinfoTab)) - - - # -- group -- - match_data_sampleinfoTab = match(rownames(data),rownames(sampleinfoTab)) - if (sum(is.na(match_data_sampleinfoTab)) > 0) { - write("ERROR: There is a problem during to match sample names from the data matrix and from the sample info (presence of NA).", stderr()) - write("You may need to use change the mode (column/row)", stderr()) - write("10 first sample names in the data matrix:", stderr()) - write(head(colnames(data)), stderr()) - write("10 first sample names in the sample info:", stderr()) - write(head(rownames(sampleinfoTab)), stderr()) - quit("no",status=10) - } - - - # -- anova -- - - # formula - grps=list() - anova_formula_s = "data ~ " - cat("\ncontrasts:\n") - for (i in 1:length(condition)) { - grps[[i]] = factor(sampleinfoTab[,condition[i]][match_data_sampleinfoTab]) - anova_formula_s = paste(anova_formula_s, "grps[[",i,"]]",anova_formula_operator, sep="") - cat(condition[i],"\t",levels(grps[[i]]),"\n") - # write("Current groups: ", stderr()) - # write(grp[[i]], stderr()) - } - anova_formula_s = substr(anova_formula_s, 1, nchar(anova_formula_s)-1) - anova_formula = as.formula(anova_formula_s) - - - - # anova - manovaObjectList = manova(anova_formula) - manovaList = summary.aov(manovaObjectList) - - # condition renaming - manovaRownames = gsub(" ","",rownames(manovaList[[1]])) - manovaNbrPvalue = length(manovaRownames)-1 - manovaRownames = manovaRownames[-(manovaNbrPvalue+1)] - - for (i in 1:length(condition)) { - manovaRownames = sub(paste("grps\\[\\[",i,"\\]\\]",sep=""),condition[i],manovaRownames) - anova_formula_s = sub(paste("grps\\[\\[",i,"\\]\\]",sep=""),condition[i],anova_formula_s) - } - - # log - cat("\nanova_formula",anova_formula_s,"\n") - - # p-value - aovPValue = sapply(manovaList,function(x){x[-(manovaNbrPvalue+1),5]}) - if(length(condition) == 1) aovPValue = t(aovPValue) - rownames(aovPValue) = paste("pvalue_",manovaRownames,sep="") - - # p-value adjusted - if(length(condition) == 1) { - aovAdjPValue = t(p.adjust(aovPValue,method=method)) - } else { - aovAdjPValue = apply(aovPValue,2,p.adjust, method=method) - } - rownames(aovAdjPValue) = paste("pvalueadjusted.",method,".",manovaRownames,sep="") - - # selection - colSumThreshold = colSums(aovAdjPValue <= threshold) - if (selection_method == "intersection") { - datafiltered = data[,colSumThreshold == nrow(aovAdjPValue )] - } else { - datafiltered = data[,colSumThreshold != 0] - } - - #data=rbind(data, aovPValue, aovAdjPValue) - data=rbind(data, aovAdjPValue) - - - if (mode == "row") { - data=t(data) - datafiltered=t(datafiltered) - } - - # -- output / return -- - write.table(data, outputdatapvalue, sep=sep, quote=F, col.names = NA) - write.table(datafiltered, outputdatafiltered, sep=sep, quote=F, col.names = NA) - - # log - cat("\nthreshold:",threshold,"\n") - cat("result:",nrow(datafiltered),"/",nrow(data),"\n") - - quit("no",status=0) -} - -# log -cat("ANOVA\n\n") -cat("Arguments\n") -args <- commandArgs(trailingOnly = TRUE) -print(args) - -listArguments = parseCommandArgs(evaluate=FALSE) -do.call(anova, listArguments) - - -
--- a/abims_anova.xml Mon Apr 04 08:46:20 2016 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,257 +0,0 @@ -<tool id="abims_anova" name="Anova" version="1.1.4"> - - <description>N-way anova. With ou Without interactions</description> - - <requirements> - <requirement type="package" version="3.1.2">R</requirement> - <requirement type="package" version="1.1_4">r-batch</requirement> - </requirements> - - <stdio> - <exit_code range="1:" level="fatal" /> - </stdio> - - <command interpreter="Rscript"> -abims_anova.r file "$input" sampleinfo "$sampleinfo" mode "$mode" -condition "c('$condition_1' -#for $i, $s in enumerate( $conditions ) -,'${s.condition}' -#end for -)" -interaction $interaction method $method threshold $threshold selection_method $selection_method sep "$sep" dec "$dec" outputdatapvalue $dataMatrixPValue outputdatafiltered $dataMatrixFiltered - </command> - - <inputs> - <param name="input" type="data" label="Data Matrix file" format="tabular" help="Matrix of numeric data with headers." /> - <param name="sampleinfo" type="data" label="Sample Metadata file" format="tabular" help="Tabular file with the data metadata : one sample per line and at least two columns : ids and one condition" /> - - <param name="mode" type="select" help="Perform the anova tests on column/row" format="text" optional="true"> - <label>Mode</label> - <option value="row">row</option> - <option value="column">column</option> - </param> - - <param name="condition_1" type="text" label="Condition" value="" help="The column name of the condition. ex: hour or treatment" optional="false" /> - <repeat name="conditions" title="Conditions for N-ways anova"> - <param name="condition" type="text" label="Condition" value="" help="The column name of the condition. ex: hour or treatment" /> - </repeat> - - <param name="interaction" type="boolean" label="Enable interaction response p-values" truevalue="T" falsevalue="F" help="Used if more than 1 conditon. The anova will produse p-value according to the interaction between your condition (ex: condition1:conditions2, condition1:conditions3, condition2:conditions3 and condition1:condition2:conditions3)" /> - - <param name="method" type="select" help="Method used to apply a correction on the pvalue because of the number of test" format="text" optional="true"> - <label>PValue adjusted method</label> - <option value="BH">BH</option> - <option value="holm">holm</option> - <option value="bonferroni">bonferroni</option> - <option value="hochberg">hochberg</option> - <option value="hommel">hommel</option> - <option value="BY">BY</option> - <option value="fdr">fdr</option> - <option value="none">none</option> - </param> - - <param name="threshold" type="float" label="Threshold" value="0.01" help="max adjusted p.value accepted" /> - - <param name="selection_method" type="select" format="text" help="Intersection: all condition p-value must be under the threshold. Union: at least condition p-value must be under the threshold. "> - <label>Selection method</label> - <option value="intersection" selected="true">intersection / strong</option> - <option value="union">union / weak</option> - </param> - - <param name="sep" type="select" format="text"> - <label>Separator of columns</label> - <option value="tabulation">tabulation</option> - <option value="semicolon">;</option> - <option value="comma">,</option> - </param> - - <param name="dec" type="text" label="Decimal separator" value="." help="" /> - - </inputs> - - <outputs> - <data name="dataMatrixPValue" format_source="input" label="${input.name}_anova_pvalue.${input.ext}"/> - <data name="dataMatrixFiltered" format_source="input" label="${input.name}_anova_filtered.${input.ext}"/> - </outputs> - - <tests> - <test> - <param name="input" value="dataMatrix.tsv"/> - <param name="sampleinfo" value="sampleMetadata.tsv"/> - <param name="mode" value="row"/> - <param name="condition_1" value="age"/> - <param name="conditions_0|condition" value="gender"/> - <param name="interaction" value="F"/> - <param name="method" value="BH"/> - <param name="threshold" value="0.05"/> - <param name="selection_method" value="union"/> - <param name="sep" value="tabulation"/> - <param name="dev" value="."/> - <output name="dataMatrixPValue" file="dataMatrix.tsv_anova_pvalue.tabular" /> - <output name="dataMatrixFiltered" file="dataMatrix.tsv_anova_filtered.tabular" /> - </test> - </tests> - - <help> - -.. class:: infomark - -**Authors** Gildas Le Corguille ABiMS - UPMC/CNRS - Station Biologique de Roscoff - gildas.lecorguille|at|sb-roscoff.fr - ---------------------------------------------------- - -===== -Anova -===== - ------------ -Description ------------ - -Analysis of variance (ANOVA) is used to analyze the differences between group means and their associated procedures, -in which the observed variance in a particular variable is partitioned into components attributable to different sources of variation. - - - ------------ -Input files ------------ - -+---------------------------+------------+ -| Parameter : num + label | Format | -+===========================+============+ -| 1 : Data Matrix file | Tabular | -+---------------------------+------------+ -| 2 : Sample Metadata file | Tabular | -+---------------------------+------------+ - - - ------------- -Output files ------------- - - - -***.anova_pvalue.tabular** - - | A tabular file which represents for each metabolite (row), the value of the intensity in each sample (column) + two columns (aovPValue and aovAdjPValue). - -***.anova_filtered.tabular** - - | The tabular file xset.anova_pvalue.tabular containing only the metabolites that have been filtered by aovAdjPValue. - - ------- - -.. class:: infomark - -The outputs ***.anova_filtered.tabular** or ***.anova_pvalue.tabular** are tabular files. You can continue your analysis using it in the following tools: - | PCA - | Hierarchical Clustering - - - ---------------------------------------------------- - ---------------- -Working example ---------------- - - -Input files ------------ - -**>A part of an example of Data Matrix file input** - - -+--------+------------------+----------------+ -| Name | Bur-eH_FSP_12 | Bur-eH_FSP_24 | -+========+==================+================+ -|M202T601| 91206595.7559783 |106808979.08546 | -+--------+------------------+----------------+ -|M234T851| 27249137.275504 |28824971.3177926| -+--------+------------------+----------------+ - -**>A part of an example of Sample Metadata file input** - - -+---------------------------+------------+------------+------------+ -| Sample name | class | time | batch | -+===========================+============+============+============+ -| Bur-eH_FSP_12 | Bur-eH | 12 | 1 | -+---------------------------+------------+------------+------------+ -| Bur-eH_FSP_24 | Bur-eH | 24 | 1 | -+---------------------------+------------+------------+------------+ -| Bur-NI_FSP_12 | Bur-NI | 12 | 2 | -+---------------------------+------------+------------+------------+ -| Bur-NI_FSP_24 | Bur-NI | 24 | 2 | -+---------------------------+------------+------------+------------+ - -Parameters ----------- - - | Mode -> **row** - | column name of condition -> **class** - | Separator of columns: -> **tabulation** - | Decimal separator -> **.** - | PValue adjusted method -> **BH** - | Threshold -> **0.001** - - - -Output files ------------- - -**Part of an example of xset.anova_filtered.tabular:** - -.. image:: anova_pvalue.png - -**Part of an example of xset.anova_pvalue.tabular:** - -.. image:: anova_filtered.png - - ---------------------------------------------------- - - ---------------------------- -Position in workflow4metabo ---------------------------- - - -**Upstream tools** - -+---------------------------+----------------------------------------+--------+------------------------+ -| Name | Output file | Format | parameter | -+===========================+========================================+========+========================+ -|xcms.diffreport |xset.diffreport.data_matrix.tsv | Tabular| Data table file | -+---------------------------+----------------------------------------+--------+------------------------+ -|CAMERA.annotateDiffreport |xset.annotatediffreport.data_matrix.tsv | Tabular| Data table file | -+---------------------------+----------------------------------------+--------+------------------------+ -|xcms.xcmsSet |sample_info.tab | Tabular| sample info table file | -+---------------------------+----------------------------------------+--------+------------------------+ - - -**Downstream tools** - -+---------------------------+---------------------------------------------------------+--------+ -| Name | Output file | Format | -+===========================+=========================================================+========+ -|PCA |xset.anova_pvalue.tabular OR xset.anova_filtered.tabular | Tabular| -+---------------------------+---------------------------------------------------------+--------+ -|Hierarchical Clustering |xset.anova_pvalue.tabular OR xset.anova_filtered.tabular | Tabular| -+---------------------------+---------------------------------------------------------+--------+ - - -**General schema of the metabolomic workflow** - -.. image:: anova_workflow.png - - </help> - - <citations> - <citation>Ronald A. Fisher in the 1930s</citation> - </citations> - -</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/galaxy/stat_anova/Makefile Tue Jun 06 09:43:23 2017 -0400 @@ -0,0 +1,23 @@ +# USAGE: make [install|clean] + +# -------- VARIABLE -------- + +OBJ=anova.tgz +DEP=abims_anova.r abims_anova.xml static test-data + + +# ------------------------ + +all: $(OBJ) + +$(OBJ): $(DEP) + tar --exclude=".svn" -zchf $@ $^ + +# ------------------------ + +install: $(OBJ) + mv *.tgz ~ + +clean: + rm *.tgz +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/galaxy/stat_anova/README.rst Tue Jun 06 09:43:23 2017 -0400 @@ -0,0 +1,16 @@ + +Changelog/News +-------------- + + +**Version 1.1.4 04/04/2016** + +- TEST: refactoring to pass planemo test using conda dependencies + + +Test Status +----------- + +Planemo test using conda: passed + +Planemo shed_test: passed
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/galaxy/stat_anova/abims_anova.r Tue Jun 06 09:43:23 2017 -0400 @@ -0,0 +1,132 @@ +#!/usr/local/public/bin/Rscript +# version="1.1" + +# date: 06-06-2012 +# update: 18-02-2014 +# **Authors** Gildas Le Corguille ABiMS - UPMC/CNRS - Station Biologique de Roscoff - gildas.lecorguille|at|sb-roscoff.fr + +# abims_anova.r version 20140218 + +library(batch) + + +# function avova +anova = function (file, sampleinfo, mode="column", condition=1, interaction=F, method="BH", threshold=0.01, selection_method="intersection", sep=";", dec=".", outputdatapvalue="anova.data.output", outputdatafiltered="anova.datafiltered.output") { + + + if (sep=="tabulation") sep="\t" + if (sep=="semicolon") sep=";" + if (sep=="comma") sep="," + + anova_formula_operator = "+" + if (interaction) anova_formula_operator = "*" + + # -- import -- + data=read.table(file, header = TRUE, row.names=1, sep = sep, quote="\"", dec = dec, fill = TRUE, comment.char="",na.strings = "NA") + + if (mode == "row") data=t(data) + + sampleinfoTab=read.table(sampleinfo, header = TRUE, row.names=1, sep = sep, quote="\"") + rownames(sampleinfoTab) = make.names(rownames(sampleinfoTab)) + + + # -- group -- + match_data_sampleinfoTab = match(rownames(data),rownames(sampleinfoTab)) + if (sum(is.na(match_data_sampleinfoTab)) > 0) { + write("ERROR: There is a problem during to match sample names from the data matrix and from the sample info (presence of NA).", stderr()) + write("You may need to use change the mode (column/row)", stderr()) + write("10 first sample names in the data matrix:", stderr()) + write(head(colnames(data)), stderr()) + write("10 first sample names in the sample info:", stderr()) + write(head(rownames(sampleinfoTab)), stderr()) + quit("no",status=10) + } + + + # -- anova -- + + # formula + grps=list() + anova_formula_s = "data ~ " + cat("\ncontrasts:\n") + for (i in 1:length(condition)) { + grps[[i]] = factor(sampleinfoTab[,condition[i]][match_data_sampleinfoTab]) + anova_formula_s = paste(anova_formula_s, "grps[[",i,"]]",anova_formula_operator, sep="") + cat(condition[i],"\t",levels(grps[[i]]),"\n") + # write("Current groups: ", stderr()) + # write(grp[[i]], stderr()) + } + anova_formula_s = substr(anova_formula_s, 1, nchar(anova_formula_s)-1) + anova_formula = as.formula(anova_formula_s) + + + + # anova + manovaObjectList = manova(anova_formula) + manovaList = summary.aov(manovaObjectList) + + # condition renaming + manovaRownames = gsub(" ","",rownames(manovaList[[1]])) + manovaNbrPvalue = length(manovaRownames)-1 + manovaRownames = manovaRownames[-(manovaNbrPvalue+1)] + + for (i in 1:length(condition)) { + manovaRownames = sub(paste("grps\\[\\[",i,"\\]\\]",sep=""),condition[i],manovaRownames) + anova_formula_s = sub(paste("grps\\[\\[",i,"\\]\\]",sep=""),condition[i],anova_formula_s) + } + + # log + cat("\nanova_formula",anova_formula_s,"\n") + + # p-value + aovPValue = sapply(manovaList,function(x){x[-(manovaNbrPvalue+1),5]}) + if(length(condition) == 1) aovPValue = t(aovPValue) + rownames(aovPValue) = paste("pvalue_",manovaRownames,sep="") + + # p-value adjusted + if(length(condition) == 1) { + aovAdjPValue = t(p.adjust(aovPValue,method=method)) + } else { + aovAdjPValue = apply(aovPValue,2,p.adjust, method=method) + } + rownames(aovAdjPValue) = paste("pvalueadjusted.",method,".",manovaRownames,sep="") + + # selection + colSumThreshold = colSums(aovAdjPValue <= threshold) + if (selection_method == "intersection") { + datafiltered = data[,colSumThreshold == nrow(aovAdjPValue )] + } else { + datafiltered = data[,colSumThreshold != 0] + } + + #data=rbind(data, aovPValue, aovAdjPValue) + data=rbind(data, aovAdjPValue) + + + if (mode == "row") { + data=t(data) + datafiltered=t(datafiltered) + } + + # -- output / return -- + write.table(data, outputdatapvalue, sep=sep, quote=F, col.names = NA) + write.table(datafiltered, outputdatafiltered, sep=sep, quote=F, col.names = NA) + + # log + cat("\nthreshold:",threshold,"\n") + cat("result:",nrow(datafiltered),"/",nrow(data),"\n") + + quit("no",status=0) +} + +# log +cat("ANOVA\n\n") +cat("Arguments\n") +args <- commandArgs(trailingOnly = TRUE) +print(args) + +listArguments = parseCommandArgs(evaluate=FALSE) +do.call(anova, listArguments) + + +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/galaxy/stat_anova/abims_anova.xml Tue Jun 06 09:43:23 2017 -0400 @@ -0,0 +1,256 @@ +<tool id="abims_anova" name="Anova" version="1.1.4"> + + <description>N-way anova. With ou Without interactions</description> + + <requirements> + <requirement type="package" version="1.1_4">r-batch</requirement> + </requirements> + + <stdio> + <exit_code range="1:" level="fatal" /> + </stdio> + + <command interpreter="Rscript"> +abims_anova.r file "$input" sampleinfo "$sampleinfo" mode "$mode" +condition "c('$condition_1' +#for $i, $s in enumerate( $conditions ) +,'${s.condition}' +#end for +)" +interaction $interaction method $method threshold $threshold selection_method $selection_method sep "$sep" dec "$dec" outputdatapvalue $dataMatrixPValue outputdatafiltered $dataMatrixFiltered + </command> + + <inputs> + <param name="input" type="data" label="Data Matrix file" format="tabular" help="Matrix of numeric data with headers." /> + <param name="sampleinfo" type="data" label="Sample Metadata file" format="tabular" help="Tabular file with the data metadata : one sample per line and at least two columns : ids and one condition" /> + + <param name="mode" type="select" help="Perform the anova tests on column/row" format="text" optional="true"> + <label>Mode</label> + <option value="row">row</option> + <option value="column">column</option> + </param> + + <param name="condition_1" type="text" label="Condition" value="" help="The column name of the condition. ex: hour or treatment" optional="false" /> + <repeat name="conditions" title="Conditions for N-ways anova"> + <param name="condition" type="text" label="Condition" value="" help="The column name of the condition. ex: hour or treatment" /> + </repeat> + + <param name="interaction" type="boolean" label="Enable interaction response p-values" truevalue="T" falsevalue="F" help="Used if more than 1 conditon. The anova will produse p-value according to the interaction between your condition (ex: condition1:conditions2, condition1:conditions3, condition2:conditions3 and condition1:condition2:conditions3)" /> + + <param name="method" type="select" help="Method used to apply a correction on the pvalue because of the number of test" format="text" optional="true"> + <label>PValue adjusted method</label> + <option value="BH">BH</option> + <option value="holm">holm</option> + <option value="bonferroni">bonferroni</option> + <option value="hochberg">hochberg</option> + <option value="hommel">hommel</option> + <option value="BY">BY</option> + <option value="fdr">fdr</option> + <option value="none">none</option> + </param> + + <param name="threshold" type="float" label="Threshold" value="0.01" help="max adjusted p.value accepted" /> + + <param name="selection_method" type="select" format="text" help="Intersection: all condition p-value must be under the threshold. Union: at least condition p-value must be under the threshold. "> + <label>Selection method</label> + <option value="intersection" selected="true">intersection / strong</option> + <option value="union">union / weak</option> + </param> + + <param name="sep" type="select" format="text"> + <label>Separator of columns</label> + <option value="tabulation">tabulation</option> + <option value="semicolon">;</option> + <option value="comma">,</option> + </param> + + <param name="dec" type="text" label="Decimal separator" value="." help="" /> + + </inputs> + + <outputs> + <data name="dataMatrixPValue" format_source="input" label="${input.name}_anova_pvalue.${input.ext}"/> + <data name="dataMatrixFiltered" format_source="input" label="${input.name}_anova_filtered.${input.ext}"/> + </outputs> + + <tests> + <test> + <param name="input" value="dataMatrix.tsv"/> + <param name="sampleinfo" value="sampleMetadata.tsv"/> + <param name="mode" value="row"/> + <param name="condition_1" value="age"/> + <param name="conditions_0|condition" value="gender"/> + <param name="interaction" value="F"/> + <param name="method" value="BH"/> + <param name="threshold" value="0.05"/> + <param name="selection_method" value="union"/> + <param name="sep" value="tabulation"/> + <param name="dev" value="."/> + <output name="dataMatrixPValue" file="dataMatrix.tsv_anova_pvalue.tabular" /> + <output name="dataMatrixFiltered" file="dataMatrix.tsv_anova_filtered.tabular" /> + </test> + </tests> + + <help> + +.. class:: infomark + +**Authors** Gildas Le Corguille ABiMS - UPMC/CNRS - Station Biologique de Roscoff - gildas.lecorguille|at|sb-roscoff.fr + +--------------------------------------------------- + +===== +Anova +===== + +----------- +Description +----------- + +Analysis of variance (ANOVA) is used to analyze the differences between group means and their associated procedures, +in which the observed variance in a particular variable is partitioned into components attributable to different sources of variation. + + + +----------- +Input files +----------- + ++---------------------------+------------+ +| Parameter : num + label | Format | ++===========================+============+ +| 1 : Data Matrix file | Tabular | ++---------------------------+------------+ +| 2 : Sample Metadata file | Tabular | ++---------------------------+------------+ + + + +------------ +Output files +------------ + + + +***.anova_pvalue.tabular** + + | A tabular file which represents for each metabolite (row), the value of the intensity in each sample (column) + two columns (aovPValue and aovAdjPValue). + +***.anova_filtered.tabular** + + | The tabular file xset.anova_pvalue.tabular containing only the metabolites that have been filtered by aovAdjPValue. + + +------ + +.. class:: infomark + +The outputs ***.anova_filtered.tabular** or ***.anova_pvalue.tabular** are tabular files. You can continue your analysis using it in the following tools: + | PCA + | Hierarchical Clustering + + + +--------------------------------------------------- + +--------------- +Working example +--------------- + + +Input files +----------- + +**>A part of an example of Data Matrix file input** + + ++--------+------------------+----------------+ +| Name | Bur-eH_FSP_12 | Bur-eH_FSP_24 | ++========+==================+================+ +|M202T601| 91206595.7559783 |106808979.08546 | ++--------+------------------+----------------+ +|M234T851| 27249137.275504 |28824971.3177926| ++--------+------------------+----------------+ + +**>A part of an example of Sample Metadata file input** + + ++---------------------------+------------+------------+------------+ +| Sample name | class | time | batch | ++===========================+============+============+============+ +| Bur-eH_FSP_12 | Bur-eH | 12 | 1 | ++---------------------------+------------+------------+------------+ +| Bur-eH_FSP_24 | Bur-eH | 24 | 1 | ++---------------------------+------------+------------+------------+ +| Bur-NI_FSP_12 | Bur-NI | 12 | 2 | ++---------------------------+------------+------------+------------+ +| Bur-NI_FSP_24 | Bur-NI | 24 | 2 | ++---------------------------+------------+------------+------------+ + +Parameters +---------- + + | Mode -> **row** + | column name of condition -> **class** + | Separator of columns: -> **tabulation** + | Decimal separator -> **.** + | PValue adjusted method -> **BH** + | Threshold -> **0.001** + + + +Output files +------------ + +**Part of an example of xset.anova_filtered.tabular:** + +.. image:: anova_pvalue.png + +**Part of an example of xset.anova_pvalue.tabular:** + +.. image:: anova_filtered.png + + +--------------------------------------------------- + + +--------------------------- +Position in workflow4metabo +--------------------------- + + +**Upstream tools** + ++---------------------------+----------------------------------------+--------+------------------------+ +| Name | Output file | Format | parameter | ++===========================+========================================+========+========================+ +|xcms.diffreport |xset.diffreport.data_matrix.tsv | Tabular| Data table file | ++---------------------------+----------------------------------------+--------+------------------------+ +|CAMERA.annotateDiffreport |xset.annotatediffreport.data_matrix.tsv | Tabular| Data table file | ++---------------------------+----------------------------------------+--------+------------------------+ +|xcms.xcmsSet |sample_info.tab | Tabular| sample info table file | ++---------------------------+----------------------------------------+--------+------------------------+ + + +**Downstream tools** + ++---------------------------+---------------------------------------------------------+--------+ +| Name | Output file | Format | ++===========================+=========================================================+========+ +|PCA |xset.anova_pvalue.tabular OR xset.anova_filtered.tabular | Tabular| ++---------------------------+---------------------------------------------------------+--------+ +|Hierarchical Clustering |xset.anova_pvalue.tabular OR xset.anova_filtered.tabular | Tabular| ++---------------------------+---------------------------------------------------------+--------+ + + +**General schema of the metabolomic workflow** + +.. image:: anova_workflow.png + + </help> + + <citations> + <citation>Ronald A. Fisher in the 1930s</citation> + </citations> + +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/galaxy/stat_anova/planemo_test.sh Tue Jun 06 09:43:23 2017 -0400 @@ -0,0 +1,11 @@ +planemo conda_install . +planemo test --install_galaxy --conda_dependency_resolution . + +#All 1 test(s) executed passed. +#abims_anova[0]: passed + + +planemo shed_test --install_galaxy -t testtoolshed + +#All 1 test(s) executed passed. +#testtoolshed.g2.bx.psu.edu/repos/lecorguille/anova/abims_anova/1.1.4[0]: passed
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/galaxy/stat_anova/test-data/dataMatrix.tsv Tue Jun 06 09:43:23 2017 -0400 @@ -0,0 +1,16 @@ +dataMatrix HU_017 HU_028 HU_034 HU_051 HU_060 HU_078 HU_091 HU_093 HU_099 HU_110 HU_130 HU_134 HU_138 HU_149 HU_152 HU_175 HU_178 HU_185 HU_204 HU_208 +HMDB03193 76043 412165 44943 27242 436566 173175 242549 57066 559869 3732 339188 471368 262271 127285 451270 212500 79673 NA 891129 43907 +HMDB01101 30689 6877586 52217 3158 10789748 229568 4763576 3878773 976436 831937 608298 1605075 72021 442510 1107705 1464339 31250 2724553 72900 32742 +HMDB10348 47259 544877 60885 34582 529874 168264 176500 76457 610110 16262 279156 524468 451573 591487 433529 161069 214392 13781 1580343 39315 +HMDB59717 357351 1030464 301983 67604 306862 1028110 1530493 270027 1378535 289677 808334 1132813 871209 895435 715190 1563158 784738 146195 994336 239030 +HMDB00822 483755 579287 1132413 157113 1577570 1469735 1085454 477909 814755 245417 610681 763706 2406336 827531 992508 569605 355321 150259 1334200 271010 +HMDB13189 2644620 727587 1661412 619181 136278 2755434 593863 837865 3526136 2003278 1608814 3446611 1941527 113937 3132404 2893445 2092753 1034666 1517319 841661 +HMDB00299 250551 1046138 456162 159386 1013302 808657 614370 250403 768004 242085 504108 1014041 1362408 1057660 1110050 566050 411886 142233 1992420 284775 +HMDB00191 560002 771533 575790 392284 888498 785428 645785 591569 960658 910201 639437 1092885 1409045 2292023 1246459 1945577 710519 773384 1061418 622898 +HMDB00518 34236 58249 85944 NA 342102 129886 175800 13154 230242 NA 440223 315368 10657 419508 48673 28361 514579 23108 867108 73831 +HMDB00715 1252089 2547452 905408 371059 4983588 5140022 2658555 814523 2558923 859466 4184204 3865723 3236644 2615560 3820724 3577833 2295288 625924 7517724 1341900 +HMDB01032 2569205 26023086 1604999 430453 8103558 26222916 257139 675754 59906109 263055 31151730 18648127 14989438 1554658 20249262 5588731 871010 15920 9120781 44276 +HMDB00208 747080 13420742 595872 1172376 7172632 3143654 4059767 1433702 5593888 5402629 2477288 3346077 4230072 7621236 8960828 10335722 7037373 1574738 3359238 2540044 +HMDB04824 374028 1144386 539206 178517 1046190 959381 605191 310260 1253319 477259 477995 825691 1157093 1089284 1411802 1020206 782673 346761 1824553 387811 +HMDB00512 53304 319783 280560 85009 1333877 556003 590779 209285 342532 198512 569970 525240 246282 1140422 542345 1171008 827723 222953 438839 85554 +HMDB00251 368600 616555 94936 622468 180988 293988 352855 767894 268331 167246 310918 1248919 577184 10985 335711 403815 80614 63393 454489 616061
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/galaxy/stat_anova/test-data/dataMatrix.tsv_anova_filtered.tabular Tue Jun 06 09:43:23 2017 -0400 @@ -0,0 +1,3 @@ + HU_017 HU_028 HU_034 HU_051 HU_060 HU_078 HU_091 HU_093 HU_099 HU_110 HU_130 HU_134 HU_138 HU_149 HU_152 HU_175 HU_178 HU_185 HU_204 HU_208 +HMDB00208 747080 13420742 595872 1172376 7172632 3143654 4059767 1433702 5593888 5402629 2477288 3346077 4230072 7621236 8960828 10335722 7037373 1574738 3359238 2540044 +HMDB00512 53304 319783 280560 85009 1333877 556003 590779 209285 342532 198512 569970 525240 246282 1140422 542345 1171008 827723 222953 438839 85554
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/galaxy/stat_anova/test-data/dataMatrix.tsv_anova_pvalue.tabular Tue Jun 06 09:43:23 2017 -0400 @@ -0,0 +1,16 @@ + HU_017 HU_028 HU_034 HU_051 HU_060 HU_078 HU_091 HU_093 HU_099 HU_110 HU_130 HU_134 HU_138 HU_149 HU_152 HU_175 HU_178 HU_185 HU_204 HU_208 pvalueadjusted.BH.age pvalueadjusted.BH.gender +HMDB03193 76043 412165 44943 27242 436566 173175 242549 57066 559869 3732 339188 471368 262271 127285 451270 212500 79673 NA 891129 43907 0.740856975457218 0.740856975457218 +HMDB01101 30689 6877586 52217 3158 10789748 229568 4763576 3878773 976436 831937 608298 1605075 72021 442510 1107705 1464339 31250 2724553 72900 32742 0.347623051099051 0.234554902330543 +HMDB10348 47259 544877 60885 34582 529874 168264 176500 76457 610110 16262 279156 524468 451573 591487 433529 161069 214392 13781 1580343 39315 0.720303175717481 0.720303175717481 +HMDB59717 357351 1030464 301983 67604 306862 1028110 1530493 270027 1378535 289677 808334 1132813 871209 895435 715190 1563158 784738 146195 994336 239030 0.252979062487671 0.517822514350462 +HMDB00822 483755 579287 1132413 157113 1577570 1469735 1085454 477909 814755 245417 610681 763706 2406336 827531 992508 569605 355321 150259 1334200 271010 0.808532959173048 0.808532959173048 +HMDB13189 2644620 727587 1661412 619181 136278 2755434 593863 837865 3526136 2003278 1608814 3446611 1941527 113937 3132404 2893445 2092753 1034666 1517319 841661 0.329174238111018 0.329174238111018 +HMDB00299 250551 1046138 456162 159386 1013302 808657 614370 250403 768004 242085 504108 1014041 1362408 1057660 1110050 566050 411886 142233 1992420 284775 0.995859884733937 0.995859884733937 +HMDB00191 560002 771533 575790 392284 888498 785428 645785 591569 960658 910201 639437 1092885 1409045 2292023 1246459 1945577 710519 773384 1061418 622898 0.15341384456659 0.15341384456659 +HMDB00518 34236 58249 85944 NA 342102 129886 175800 13154 230242 NA 440223 315368 10657 419508 48673 28361 514579 23108 867108 73831 0.439012867631325 0.596200901535843 +HMDB00715 1252089 2547452 905408 371059 4983588 5140022 2658555 814523 2558923 859466 4184204 3865723 3236644 2615560 3820724 3577833 2295288 625924 7517724 1341900 0.814406453193777 0.814406453193777 +HMDB01032 2569205 26023086 1604999 430453 8103558 26222916 257139 675754 59906109 263055 31151730 18648127 14989438 1554658 20249262 5588731 871010 15920 9120781 44276 0.288354536353544 0.288354536353544 +HMDB00208 747080 13420742 595872 1172376 7172632 3143654 4059767 1433702 5593888 5402629 2477288 3346077 4230072 7621236 8960828 10335722 7037373 1574738 3359238 2540044 0.659785284053633 0.00376251274734483 +HMDB04824 374028 1144386 539206 178517 1046190 959381 605191 310260 1253319 477259 477995 825691 1157093 1089284 1411802 1020206 782673 346761 1824553 387811 0.646714644805001 0.646714644805001 +HMDB00512 53304 319783 280560 85009 1333877 556003 590779 209285 342532 198512 569970 525240 246282 1140422 542345 1171008 827723 222953 438839 85554 0.13976111393526 0.0491480895853803 +HMDB00251 368600 616555 94936 622468 180988 293988 352855 767894 268331 167246 310918 1248919 577184 10985 335711 403815 80614 63393 454489 616061 0.565910223149305 0.565910223149305
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/galaxy/stat_anova/test-data/sampleMetadata.tsv Tue Jun 06 09:43:23 2017 -0400 @@ -0,0 +1,21 @@ +sampleMetadata injectionOrder mode age bmi gender +HU_017 2 pos 40-50 23.03 M +HU_028 7 pos 40-50 23.92 F +HU_034 9 pos 50-60 23.37 M +HU_051 20 pos 20-30 23.23 F +HU_060 24 pos 50-60 28.72 F +HU_078 34 pos 40-50 25.18 M +HU_091 42 pos 60-70 26.12 M +HU_093 43 pos 50-60 21.71 M +HU_099 46 pos 20-30 21.3 M +HU_110 53 pos 50-60 20.9 F +HU_130 63 pos 30-40 26.06 M +HU_134 67 pos 40-50 22.89 M +HU_138 68 pos 40-50 21.88 M +HU_149 72 pos 30-40 19.49 F +HU_152 75 pos 20-30 17.58 F +HU_175 87 pos 30-40 21.26 F +HU_178 88 pos 60-70 32.87 F +HU_185 95 pos 40-50 21.09 F +HU_204 104 pos 30-40 29.06 M +HU_208 106 pos 20-30 18.61 F
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/galaxy/stat_anova/tool_dependencies.xml Tue Jun 06 09:43:23 2017 -0400 @@ -0,0 +1,9 @@ +<?xml version="1.0"?> +<tool_dependency> + <package name="R" version="3.1.2"> + <repository changeset_revision="4d2fd1413b56" name="package_r_3_1_2" owner="iuc" toolshed="https://toolshed.g2.bx.psu.edu" /> + </package> + <package name="r-batch" version="1.1_4"> + <repository changeset_revision="e8a964ca8656" name="package_r_batch_1_1_4" owner="lecorguille" toolshed="https://toolshed.g2.bx.psu.edu" /> + </package> +</tool_dependency>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/install/package_r_batch/tool_dependencies.xml Tue Jun 06 09:43:23 2017 -0400 @@ -0,0 +1,30 @@ +<?xml version="1.0"?> +<tool_dependency> + <package name="R" version="3.1.2"> + <repository changeset_revision="4d2fd1413b56" name="package_r_3_1_2" owner="iuc" prior_installation_required="True" toolshed="https://toolshed.g2.bx.psu.edu" /> + </package> + + <package name="r-batch" version="1.1_4"> + <install version="1.0"> + <actions> + <action type="setup_r_environment"> + <repository changeset_revision="4d2fd1413b56" name="package_r_3_1_2" owner="iuc" toolshed="https://toolshed.g2.bx.psu.edu"> + <package name="R" version="3.1.2" /> + </repository> + + <package>http://application.sb-roscoff.fr/download/w4m/cran-archive/package_r_batch_1_1_4//batch_1.1-4.tar.gz</package> + </action> + </actions> + </install> + <readme> +batch: https://cran.r-project.org/web/packages/batch/index.html +batch: Batching Routines in Parallel and Passing Command-Line Arguments to R + +Functions to allow you to easily pass command-line arguments into R, and functions to aid in submitting your R code in parallel on a cluster and joining the results afterward (e.g. multiple parameter values for simulations running in parallel, splitting up a permutation test in parallel, etc.). See ‘parseCommandArgs(...)’ for the main example of how to use this package. + +Author: Thomas Hoffmann tjhoffm at gmail.com + + + </readme> + </package> +</tool_dependency>
--- a/planemo_test.sh Mon Apr 04 08:46:20 2016 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,6 +0,0 @@ -planemo conda_install . -planemo test --install_galaxy --conda_dependency_resolution . - -#All 1 test(s) executed passed. -#abims_anova[0]: passed -
--- a/test-data/dataMatrix.tsv Mon Apr 04 08:46:20 2016 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,16 +0,0 @@ -dataMatrix HU_017 HU_028 HU_034 HU_051 HU_060 HU_078 HU_091 HU_093 HU_099 HU_110 HU_130 HU_134 HU_138 HU_149 HU_152 HU_175 HU_178 HU_185 HU_204 HU_208 -HMDB03193 76043 412165 44943 27242 436566 173175 242549 57066 559869 3732 339188 471368 262271 127285 451270 212500 79673 NA 891129 43907 -HMDB01101 30689 6877586 52217 3158 10789748 229568 4763576 3878773 976436 831937 608298 1605075 72021 442510 1107705 1464339 31250 2724553 72900 32742 -HMDB10348 47259 544877 60885 34582 529874 168264 176500 76457 610110 16262 279156 524468 451573 591487 433529 161069 214392 13781 1580343 39315 -HMDB59717 357351 1030464 301983 67604 306862 1028110 1530493 270027 1378535 289677 808334 1132813 871209 895435 715190 1563158 784738 146195 994336 239030 -HMDB00822 483755 579287 1132413 157113 1577570 1469735 1085454 477909 814755 245417 610681 763706 2406336 827531 992508 569605 355321 150259 1334200 271010 -HMDB13189 2644620 727587 1661412 619181 136278 2755434 593863 837865 3526136 2003278 1608814 3446611 1941527 113937 3132404 2893445 2092753 1034666 1517319 841661 -HMDB00299 250551 1046138 456162 159386 1013302 808657 614370 250403 768004 242085 504108 1014041 1362408 1057660 1110050 566050 411886 142233 1992420 284775 -HMDB00191 560002 771533 575790 392284 888498 785428 645785 591569 960658 910201 639437 1092885 1409045 2292023 1246459 1945577 710519 773384 1061418 622898 -HMDB00518 34236 58249 85944 NA 342102 129886 175800 13154 230242 NA 440223 315368 10657 419508 48673 28361 514579 23108 867108 73831 -HMDB00715 1252089 2547452 905408 371059 4983588 5140022 2658555 814523 2558923 859466 4184204 3865723 3236644 2615560 3820724 3577833 2295288 625924 7517724 1341900 -HMDB01032 2569205 26023086 1604999 430453 8103558 26222916 257139 675754 59906109 263055 31151730 18648127 14989438 1554658 20249262 5588731 871010 15920 9120781 44276 -HMDB00208 747080 13420742 595872 1172376 7172632 3143654 4059767 1433702 5593888 5402629 2477288 3346077 4230072 7621236 8960828 10335722 7037373 1574738 3359238 2540044 -HMDB04824 374028 1144386 539206 178517 1046190 959381 605191 310260 1253319 477259 477995 825691 1157093 1089284 1411802 1020206 782673 346761 1824553 387811 -HMDB00512 53304 319783 280560 85009 1333877 556003 590779 209285 342532 198512 569970 525240 246282 1140422 542345 1171008 827723 222953 438839 85554 -HMDB00251 368600 616555 94936 622468 180988 293988 352855 767894 268331 167246 310918 1248919 577184 10985 335711 403815 80614 63393 454489 616061
--- a/test-data/dataMatrix.tsv_anova_filtered.tabular Mon Apr 04 08:46:20 2016 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,3 +0,0 @@ - HU_017 HU_028 HU_034 HU_051 HU_060 HU_078 HU_091 HU_093 HU_099 HU_110 HU_130 HU_134 HU_138 HU_149 HU_152 HU_175 HU_178 HU_185 HU_204 HU_208 -HMDB00208 747080 13420742 595872 1172376 7172632 3143654 4059767 1433702 5593888 5402629 2477288 3346077 4230072 7621236 8960828 10335722 7037373 1574738 3359238 2540044 -HMDB00512 53304 319783 280560 85009 1333877 556003 590779 209285 342532 198512 569970 525240 246282 1140422 542345 1171008 827723 222953 438839 85554
--- a/test-data/dataMatrix.tsv_anova_pvalue.tabular Mon Apr 04 08:46:20 2016 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,16 +0,0 @@ - HU_017 HU_028 HU_034 HU_051 HU_060 HU_078 HU_091 HU_093 HU_099 HU_110 HU_130 HU_134 HU_138 HU_149 HU_152 HU_175 HU_178 HU_185 HU_204 HU_208 pvalueadjusted.BH.age pvalueadjusted.BH.gender -HMDB03193 76043 412165 44943 27242 436566 173175 242549 57066 559869 3732 339188 471368 262271 127285 451270 212500 79673 NA 891129 43907 0.740856975457218 0.740856975457218 -HMDB01101 30689 6877586 52217 3158 10789748 229568 4763576 3878773 976436 831937 608298 1605075 72021 442510 1107705 1464339 31250 2724553 72900 32742 0.347623051099051 0.234554902330543 -HMDB10348 47259 544877 60885 34582 529874 168264 176500 76457 610110 16262 279156 524468 451573 591487 433529 161069 214392 13781 1580343 39315 0.720303175717481 0.720303175717481 -HMDB59717 357351 1030464 301983 67604 306862 1028110 1530493 270027 1378535 289677 808334 1132813 871209 895435 715190 1563158 784738 146195 994336 239030 0.252979062487671 0.517822514350462 -HMDB00822 483755 579287 1132413 157113 1577570 1469735 1085454 477909 814755 245417 610681 763706 2406336 827531 992508 569605 355321 150259 1334200 271010 0.808532959173048 0.808532959173048 -HMDB13189 2644620 727587 1661412 619181 136278 2755434 593863 837865 3526136 2003278 1608814 3446611 1941527 113937 3132404 2893445 2092753 1034666 1517319 841661 0.329174238111018 0.329174238111018 -HMDB00299 250551 1046138 456162 159386 1013302 808657 614370 250403 768004 242085 504108 1014041 1362408 1057660 1110050 566050 411886 142233 1992420 284775 0.995859884733937 0.995859884733937 -HMDB00191 560002 771533 575790 392284 888498 785428 645785 591569 960658 910201 639437 1092885 1409045 2292023 1246459 1945577 710519 773384 1061418 622898 0.15341384456659 0.15341384456659 -HMDB00518 34236 58249 85944 NA 342102 129886 175800 13154 230242 NA 440223 315368 10657 419508 48673 28361 514579 23108 867108 73831 0.439012867631325 0.596200901535843 -HMDB00715 1252089 2547452 905408 371059 4983588 5140022 2658555 814523 2558923 859466 4184204 3865723 3236644 2615560 3820724 3577833 2295288 625924 7517724 1341900 0.814406453193777 0.814406453193777 -HMDB01032 2569205 26023086 1604999 430453 8103558 26222916 257139 675754 59906109 263055 31151730 18648127 14989438 1554658 20249262 5588731 871010 15920 9120781 44276 0.288354536353544 0.288354536353544 -HMDB00208 747080 13420742 595872 1172376 7172632 3143654 4059767 1433702 5593888 5402629 2477288 3346077 4230072 7621236 8960828 10335722 7037373 1574738 3359238 2540044 0.659785284053633 0.00376251274734483 -HMDB04824 374028 1144386 539206 178517 1046190 959381 605191 310260 1253319 477259 477995 825691 1157093 1089284 1411802 1020206 782673 346761 1824553 387811 0.646714644805001 0.646714644805001 -HMDB00512 53304 319783 280560 85009 1333877 556003 590779 209285 342532 198512 569970 525240 246282 1140422 542345 1171008 827723 222953 438839 85554 0.13976111393526 0.0491480895853803 -HMDB00251 368600 616555 94936 622468 180988 293988 352855 767894 268331 167246 310918 1248919 577184 10985 335711 403815 80614 63393 454489 616061 0.565910223149305 0.565910223149305
--- a/test-data/sampleMetadata.tsv Mon Apr 04 08:46:20 2016 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,21 +0,0 @@ -sampleMetadata injectionOrder mode age bmi gender -HU_017 2 pos 40-50 23.03 M -HU_028 7 pos 40-50 23.92 F -HU_034 9 pos 50-60 23.37 M -HU_051 20 pos 20-30 23.23 F -HU_060 24 pos 50-60 28.72 F -HU_078 34 pos 40-50 25.18 M -HU_091 42 pos 60-70 26.12 M -HU_093 43 pos 50-60 21.71 M -HU_099 46 pos 20-30 21.3 M -HU_110 53 pos 50-60 20.9 F -HU_130 63 pos 30-40 26.06 M -HU_134 67 pos 40-50 22.89 M -HU_138 68 pos 40-50 21.88 M -HU_149 72 pos 30-40 19.49 F -HU_152 75 pos 20-30 17.58 F -HU_175 87 pos 30-40 21.26 F -HU_178 88 pos 60-70 32.87 F -HU_185 95 pos 40-50 21.09 F -HU_204 104 pos 30-40 29.06 M -HU_208 106 pos 20-30 18.61 F
--- a/tool_dependencies.xml Mon Apr 04 08:46:20 2016 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,9 +0,0 @@ -<?xml version="1.0"?> -<tool_dependency> - <package name="R" version="3.1.2"> - <repository changeset_revision="c987143177d4" name="package_r_3_1_2" owner="iuc" toolshed="https://toolshed.g2.bx.psu.edu" /> - </package> - <package name="r-batch" version="1.1_4"> - <repository changeset_revision="e8a964ca8656" name="package_r_batch_1_1_4" owner="lecorguille" toolshed="https://toolshed.g2.bx.psu.edu" /> - </package> -</tool_dependency>