Mercurial > repos > vmarcon > pcafactominer
changeset 0:7acfb3bdad66 draft default tip
planemo upload commit a2411926bebc2ca3bb31215899a9f18a67e59556
| author | vmarcon |
|---|---|
| date | Thu, 18 Jan 2018 07:57:36 -0500 |
| parents | |
| children | |
| files | LICENSE pcaFactoMineR.xml pcaFactoMineR_functions.R pcaFactoMineR_galaxy.R test-data/decathlon.tsv test-data/log_file test-data/output_file |
| diffstat | 7 files changed, 1464 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/LICENSE Thu Jan 18 07:57:36 2018 -0500 @@ -0,0 +1,674 @@ + GNU GENERAL PUBLIC LICENSE + Version 3, 29 June 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/> + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU General Public License is a free, copyleft license for +software and other kinds of works. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. By contrast, +the GNU General Public License is intended to guarantee your freedom to +share and change all versions of a program--to make sure it remains free +software for all its users. We, the Free Software Foundation, use the +GNU General Public License for most of our software; it applies also to +any other work released this way by its authors. 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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pcaFactoMineR.xml Thu Jan 18 07:57:36 2018 -0500 @@ -0,0 +1,335 @@ +<!--# Copyright (C) 2017 INRA +# This program is free software: you can redistribute it and/or modify +# it under the terms of the GNU General Public License as published by +# the Free Software Foundation, either version 3 of the License, or +# (at your option) any later version. +# +# This program is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +# GNU General Public License for more details. +# +# You should have received a copy of the GNU General Public License +# along with this program. If not, see http://www.gnu.org/licenses/. +#--> + +<tool id="pcafactominer" name="PCAFactoMineR" version="1.0.0"> + <description>Realize a PCA analysis using FactoMineR package</description> + <requirements> + <requirement type="package" version="1.38" >r-factominer</requirement> + <requirement type="package">r-base</requirement> + <requirement type="package">bioconductor-pcamethods</requirement> + <requirement type="package">r-batch</requirement> + </requirements> + <stdio> + <!-- Anything other than zero is an error --> + <exit_code range="1:" level="fatal" /> + <exit_code range=":-1" level="fatal" /> + </stdio> + <command interpreter="Rscript"><![CDATA[ + pcaFactoMineR_galaxy.R + datafile '${datafile}' + npc '${npc}' + #if str( $condPlot.plotOptions ) == "yes": + + plotev '${condPlot.plotev}' + plotcontrib '${condPlot.plotcontrib}' + plotindiv '${condPlot.condScore.plotindiv}' + + #if str( $condPlot.condScore.plotindiv ) == "yes": + colorfactor '${condPlot.condScore.condColor.colorfactor}' + #if str( $condPlot.condScore.condColor.colorfactor ) == "yes": + samplemetadata '${condPlot.condScore.condColor.samplemetadata}' + factor '${condPlot.condScore.condColor.factor}' + #else : + samplemetadata "None" + factor "None" + #end if + #else : + colorfactor yes + samplemetadata "None" + factor "None" + #end if + + plotvar '${condPlot.condLoading.plotvar}' + + #if str( $condPlot.condLoading.plotvar ) == "yes": + contribh '${condPlot.condLoading.contribh}' + contribv '${condPlot.condLoading.contribv}' + #else : + contribh 0 + contribv 0 + #end if + + #else : + plotev yes + plotcontrib yes + plotindiv yes + colorfactor no + samplemetadata "None" + factor "None" + plotvar yes + contribh 0 + contribv 0 + #end if + + #if str( $condGraphical.graphicalOptions ) == "yes": + title '${condGraphical.title}' + pch '${condGraphical.pch}' + pcv '${condGraphical.pcv}' + tc '${condGraphical.tc}' + #else : + title "PCA" + pch 1 + pcv 2 + tc 1 + #end if + varinline '${varinline}' + + ## Outputs + logOut '${log_file}' + outgraphpdf '${output_file}' + ]]></command> + <inputs> + <param name="datafile" type="data" label="Data matrix" help="Precise below if the variable are in line or column" format="tabular,csv" /> + <param name="npc" label="Number of principal components" type="integer" value="2" min="2" help="" /> + <conditional name="condPlot"> + <param name="plotOptions" type="select" label="Plot Options" help="If no, it will create the 4 plot and take the default parameters"> + <option value="no" selected="true">No</option> + <option value="yes">Yes</option> + </param> + <when value="yes"> + <param name="plotev" type="select" label="Eigenvalue plot" help="Eigenvalue and percentage of explained variance plots"> + <option value="yes" selected="true"> Yes </option> + <option value="no"> No </option> + </param> + <param name="plotcontrib" type="select" label="Contribution plot" help=""> + <option value="yes" selected="true"> Yes </option> + <option value="no"> No </option> + </param> + <conditional name="condScore"> + <param name="plotindiv" label="Score plot" type="select" help=""> + <option value="yes" selected="true"> Yes </option> + <option value="no"> No </option> + </param> + <when value="yes"> + <conditional name="condColor"> + <param name="colorfactor" label="Factor color" type="select" help="Colouring of observations according to levels of qualitative variable (biological factor of interest)"> + <option value="no" selected="true"> No </option> + <option value="yes"> Yes </option> + </param> + <when value="yes"> + <param name="samplemetadata" type="data" label="Factor file" help="File with Biological Factor(s)" format="tabular,csv" /> + <param name="factor" label="Name of the column of the factor matrix corresponding to the qualitative variable" type="text" value="None" help="" /> + </when> + <when value="no"></when> + </conditional> + </when> + <when value="no"></when> + </conditional> + <conditional name="condLoading"> + <param name="plotvar" label="Loading plot" type="select" help=""> + <option value="yes" selected="true"> Yes </option> + <option value="no"> No </option> + </param> + <when value="yes"> + <param name="contribh" label="Contribution threshold (abscissa)" type="float" value="0" help="Contribution threshold for loading plot (Principal component displayed in the abscissa axis)" /> + <param name="contribv" label="Contribution threshold (ordinate)" type="float" value="0" help="Contribution threshold for loading plot (Principal component displayed in the ordinate axis)" /> + </when> + <when value="no"></when> + </conditional> + </when> + <when value="no"></when> + </conditional> + <conditional name="condGraphical"> + <param name="graphicalOptions" type="select" label="GraphicalOptions" help="If not, it will take the default parameters"> + <option value="no" selected="true">No</option> + <option value="yes">Yes</option> + </param> + <when value="yes"> + <param name="title" type="text" label="Title" help="Title printed on all plots; if none, leave 'PCA'" value="PCA" /> + <param name="pch" label="Horizontal Principal Component" type="integer" value="1" help="Principal component displayed on the abscissa" /> + <param name="pcv" label="Vertical Principal Component" help="Principal component displayed on the ordinate" type="integer" value="2" /> + <param name="tc" label="Numeric character expansion factor" type="float" value="1.0" min="0.5" help="A value greater than 1 increases and a value lower than 1 decreases character size" /> + </when> + <when value="no"></when> + </conditional> + <param name="varinline" type="select" multiple="false" display="radio" label="Variable in line or column?"> + <option value="yes">Line</option> + <option value="no">Column</option> + </param> + </inputs> + <outputs> + <data name="log_file" format="html" label="${tool.name}_log" /> + <data name="output_file" label="${tool.name}_graph" format="pdf" /> + </outputs> + <tests> + <test> + <param name="datafile" value="decathlon.tsv"/> + <param name="npc" value="2"/> + <conditional name="condPlot"> + <param name="plotOptions" value="no"/> + </conditional> + <conditional name="condGraphical"> + <param name="graphicalOptions" value="no"/> + </conditional> + <param name="varinline" value="no"/> + <output name="log_file" file="log_file"/> + <output name="output_file" file="output_file" compare="sim_size"/> + </test> + </tests> + <help><![CDATA[ + +=== +PCA +=== + +----------- +Description +----------- + + - This tool is part of a set of statistical tools made by members of the BIOS4BIOL group ("Normalization", "Summary statistics", "Hierarchical clustering" and "PCAFactoMineR"). + - Please use the Normalization module that come with the suite before using this module. + +What it does: + - Principal Component Analysis (PCA) as done in the FactoMineR package + +------ + +----------- +Input files +----------- + ++---------------------------+------------+ +| Parameter : num + label | Format | ++===========================+============+ +| 1 : data matrix | tabular | ++---------------------------+------------+ + +---------- +Parameters +---------- + +Data matrix + | see "Input files" section above + | + +Number of principal component + | How many principal components include in the PCA model? + | + +(?)Plot options + | Show (or not) more options for the plots + | + +Eigenvalue plot + | Eigenvalue and percentage of explained variance plots. Default value is "Yes" + | + +Contribution plot + | Contribution plot. Default value is "Yes" + | + +Score plot + | Score plot" plot. Default value is "Yes" + | + +Factor color + | Colouring of observations. Default value is "Yes" + | + +Factor file + | File containing the biological factor (qualitative variable) to color observations according to levels of this + | + +Factor + | Name of the column containing the biological factor + | + +Loading plot + | Loading plot. Default value is "Yes" + | + +Contribution threshold (abscissa) + | Contribution threshold for loading plot: principal component displayed in the abscissa axis + | + +Contribution threshold (ordinate) + | Contribution threshold for loading plot: principal component displayed in the ordinate axis + | + +(?)Graphical options + | Show (or not) more graphical options + | + +Title + | Title printed on all plots; if none, leave 'PCA'" value="PCA" + | + +Numeric character expansion factor + | A value greater than 1 increases and a value lower than 1 decreases character size + | + +Horizontal Principal Component + | Principal component displayed on the abscissa + | + +Vertical Principal Component + | Principal component displayed on the ordinate + | + +Variable Line/Column + | Variable in line or in column in the input file. Default value is "Line" + | + +------------ +Output files +------------ + +PCAFactoMineR_graph (pdf output) + | + +PCAFactoMineR_log + | + +------ + +**Authors** Marie Tremblay-Franco (marie.tremblay-franco@inra.fr), Jean-Francois Martin (jean-francois.martin@inra.fr), Sandrine Laguerre (laguerre@insa-toulouse.fr) and Valentin Marcon (valentin.marcon@inra.fr) + +Contact : support.sigenae@inra.fr + +E-learning available : Not yet. + +.. class:: infomark + +------------- +Please cite : +------------- + +- (Depending on the help provided you can cite us in acknowledgements, references or both.) + +Acknowledgements + | We wish to thank the SIGENAE group and the statistical CATI BIOS4Biol group : Marie Tremblay-Franco, Jean-Francois Martin, Sandrine Laguerre. + | Re-packaging was provided by Valentin Marcon (INRA, Migale platform http://migale.jouy.inra.fr), as part of the IFB project 'Galaxy For Life Science' (http://www.france-bioinformatique.fr/fr) + | + +References + | SIGENAE [http://www.sigenae.org/] + | + + ]]></help> + <citations> + <citation type="bibtex"> + @article{10.18637/jss.v025.i01, + title = {{FactoMineR}: A Package for Multivariate Analysis}, + author = {S\'ebastien Le and Julie Josse and Fran\c{c}ois Husson}, + journal = {Journal of Statistical Software}, + year = {2008}, + volume = {25}, + number = {1}, + pages = {1--18}, + doi = {10.18637/jss.v025.i01}, + url = {https://dx.doi.org/10.18637/jss.v025.i01}} + </citation> + </citations> +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pcaFactoMineR_functions.R Thu Jan 18 07:57:36 2018 -0500 @@ -0,0 +1,274 @@ +#################### fonctions utilisées ##################################################### + +standardisation <- function(rawX,centrage=TRUE,scaling=c("none","uv","pareto")) +{ + # rawX : matrice nxp contenant les données brutes + # Forme à confirmer avec SLA colonne 1 = identifiant,colonne 2 = facteur biologique??? + # Si oui "supprimer" ces 2 colonnes pour n'avoir que variables quantitatives + # centrage = parametre booleen (TRUE/FALSE),par défaut = TRUE,indiquant si centrage donnees à faire + # scaling = nom de la methode de standardisation à appliquer aux donnees + # none = aucune standardisation + # uv = division par ecart type + # pareto = division par racine carree ecart type + # scaledX : matrice nxp contenant les variables quantitatives standardisees (centrage +/- scaling) + scaledX <- prep(rawX,center=centrage,scale=scaling) + return(scaledX) +} + +############################################################################################### +plot_ebouli <- function(res.PCA,mt,cexc) +{ + # res.PCA résultat de l'ACP est renvoyé par la fonction PCA (factoMineR) de type list contient + # l'ensemble des résultats dont les valeurs propres et % variance assicées à chaque cp + # La fonction plot les valeurs propres et les % de variance + # expliquée par chaque composante et la variance cumulée + + eig <- res.PCA$eig + barplot(eig[[1]]) + #abline(h=1) + title(main=mt,sub="Eigen values") + barplot(eig[[2]],ylim=c(0,100)) + points(eig[[3]],type="b") + title(main=mt,sub="Variance explained",cex=cexc) + +} + +############################################################################################### +plot.contrib <- function(res.PCA,mt,cexc) +{ + # Fonction de plot des contributions sur les n composantes + # principales choisies par l'utilisateur (lastpc) + # En entrée,la fonction prend le résultats de l'ACP FactoMineR de type list + + lastpc <- dim(res.PCA$var$contrib)[2] + ## plot contributions + contrib <- res.PCA$var$contrib + for (c in 1:lastpc) { + barplot(quantile(contrib[,c],probs=seq(0,1,0.025))) + title(main=mt,sub=paste("Quantile plot Contrib PC",c,sep=""),cex=cexc) + barplot(contrib[order(contrib[,c]),1]) + title(main=mt,sub=paste("Contributions PC",c,sep=""),cex=cexc) + } +} + +############################################################################################### +pca.var <- function(res.PCA,contribmin=c(0,0),mt,cexc,linev=3,plotax=c(1,2)) +{ + # Loading plot avec eventuellement selection des variables par leurs contributions + # En entrée,la fonction prend le résultats de l'ACP FactoMineR de type list + # On passe en arguments : les contributions pour les 2 axes définis par l'utilisateur, + # le titre du graphique,la taille des caractères (cex), + # ??? est-ce que la fonction doit plotter toutes les composantes ??? + + ### sélection des variables sur leur contribution. + # les valeurs des contributions par défaut (0,0) permettent d'afficher + # toutes les variables. + selvar=c(which(res.PCA$var$contrib[,plotax[1]]>contribmin[1]), + which(res.PCA$var$contrib[,plotax[2]]>contribmin[2])) + selvar <- selvar[!duplicated(selvar)] + fres.PCA <- res.PCA + fres.PCA$var$coord <- res.PCA$var$coord[selvar,] + fres.PCA$var$cor <- res.PCA$var$cor[selvar,] + fres.PCA$var$cos2 <- res.PCA$var$cos2[selvar,] + fres.PCA$var$contrib <- res.PCA$var$contrib[selvar,] + + #### Plot du cercle des corrélations + plot.PCA(fres.PCA,choix="var",cex=cexc,axes=plotax,title=NULL, habillage=1) + title(main = mt,line = linev,cex=cexc) +} + +############################################################################################### +pca.indiv <- function(res.PCA,hb,facteur=NULL,contribmin=c(0,0),mt,cexc,linev=3,plotax=c(1,2)) +{ + # Espace des individus + # En entrée,la fonction prend le résultats de l'ACP FactoMineR de type list + # On passe en arguments : les contributions pour les 2 axes définis par l'utilisateur, + # le titre du graphique,la taille des caractères (cex), + # ??? est-ce que la fonction doit plotter toutes les composantes ??? + selvar=c(which(res.PCA$var$contrib[,plotax[1]]>contribmin[1]), + which(res.PCA$var$contrib[,plotax[2]]>contribmin[2])) + + fres.PCA <- res.PCA + fres.PCA$var$coord <- res.PCA$var$coord[selvar,] + fres.PCA$var$cor <- res.PCA$var$cor[selvar,] + fres.PCA$var$cos2 <- res.PCA$var$cos2[selvar,] + fres.PCA$var$contrib <- res.PCA$var$contrib[selvar,] + + #### Plot l'espace des individus + if (hb ==1 ) + { + aa <- cbind.data.frame(facteur,res.PCA$ind$coord) + bb <- coord.ellipse(aa,bary=TRUE,level.conf=0.99) + + colVal = rainbow(length(unique(facteur))) + plot.PCA(fres.PCA,choix="ind",habillage=1,cex=cexc,axes=plotax,title=NULL,invisible="quali") + title(main = mt,line = linev,cex=cexc) + + plot.PCA(fres.PCA,choix="ind",habillage=1,label="none",cex=cexc,axes=plotax,title=NULL,ellipse=bb) + title(main = mt,line = linev,cex=cexc) + } + else + { + plot.PCA(fres.PCA,choix="ind",cex=cexc,axes=plotax,title=NULL) + title(main = mt,line = linev,cex=cexc) + } +} + +############################################################################################### +## MODIFICATIONS 15062017 +## Suppression standardisation car fonction externe +## Concatenation samplemetadata et datamatrix avec merge si pas meme ordre de tri +## HYPOTHESES : 1) datamatrix : nxp et 2) colonne 1 = identifiants individus +############################################################################################### + +pca.main <- function(ids,bioFact,ncp,hb=0,minContribution=c(0,0),mainTitle=NULL,textSize=0.5,linev=3, + principalPlane=c(1,2),eigenplot=0,contribplot=0,scoreplot=0,loadingplot=0,nomGraphe, + variable_in_line=0,log_file) +{ + + res<-NULL + + ## Variable in line or column? + if (variable_in_line==1){ + column_use="individual" + line_use="variable" + } else { + line_use="individual" + column_use="variable" + } + + + ## Fonction d'écriture du fichier de log + +log_error=function(message="") { + cat("<HTML><HEAD><TITLE>PCA FactoMineR report</TITLE></HEAD><BODY>\n",file=log_file,append=F,sep="") + cat("⚠ An error occurred while trying to read your table.\n<BR>",file=log_file,append=T,sep="") + cat("Please check that:\n<BR>",file=log_file,append=T,sep="") + cat("<UL>\n",file=log_file,append=T,sep="") + cat(" <LI> the table you want to process contains the same number of columns for each line</LI>\n",file=log_file,append=T,sep="") + cat(" <LI> the first line of your table is a header line (specifying the name of each ",column_use,")</LI>\n",file=log_file,append=T,sep="") + cat(" <LI> the first column of your table specifies the name of each ",line_use,"</LI>\n",file=log_file,append=T,sep="") + cat(" <LI> both individual and variable names should be unique</LI>\n",file=log_file,append=T,sep="") + cat(" <LI> each value is separated from the other by a <B>TAB</B> character</LI>\n",file=log_file,append=T,sep="") + cat(" <LI> except for first line and first column, table should contain a numeric value</LI>\n",file=log_file,append=T,sep="") + cat(" <LI> this value may contain character '.' as decimal separator </LI>\n",file=log_file,append=T,sep="") + cat("</UL>\n",file=log_file,append=T,sep="") + cat("-------<BR>\nError messages recieved :<BR><FONT color=red>\n",conditionMessage(message),"</FONT>\n",file=log_file,append=T,sep="") + cat("</BODY></HTML>\n",file=log_file,append=T,sep="") + q(save="no",status=1) +} + + # Sortie graphique + if (eigenplot==1 || contribplot==1 || scoreplot==1 || loadingplot==1) + pdf(nomGraphe,onefile=TRUE) + + # Verify data +verif_data=function(){ + if (length(dim(ids)) != 2 | ncol(ids) < 2 | nrow(ids) < 2) + log_error(simpleCondition("The table on which you want to do PCA must be a data table with at least 2 rows and 2 columns.")) + + tab=as.matrix(data) + cell.with.na=c() + colstart=2-variable_in_line # + for (i in colstart:ncol(tab)) { + na.v1=is.na(tab[,i]) + na.v2=is.na(as.numeric(tab[,i])) + if (sum(na.v1)!=sum(na.v2)) { + sel=which(na.v1!=na.v2) + sel=sel[1] + value=tab[sel,i] + log_error(simpleCondition( + paste("Column '",colnames(tab)[i],"' of your table contains non numeric values. Please check its content (on line #",sel," : value='",value,"'). Maybe you will need to specify that variable are in column.",sep="") + )) + } + if (length(cell.with.na)==0 & sum(na.v1)!=0) { + cell.with.na=c(i,which(na.v1)[1]) + } + } +} + + + ## Disposition matrice de donnees + ## Transposition si variables en ligne + Tids <- ids + if (variable_in_line == 1) + { + Tids <- Tids[,-1] + Tids <- t(Tids) + Tids <- data.frame(rownames(Tids), Tids) + colnames(Tids)[1] <- "Sample" + } + rownames(Tids) <- as.character(Tids[,1]) + + + ## suivant la presence variable qualitative (hb=1),l'appel a la fonction PCA est modifié + if (hb==1) + { + ## Concatenation + data <- merge(bioFact,Tids,by.x=1,by.y=1) + rownames(data) <- as.character(data[,1]) + ## Suppression identifiants individus + data <- data[,-1] + data[,1] <- as.factor(data[,1]) + facteur <- as.factor(bioFact[,-1]) + verif_data() + + ## Analyse + res <- PCA(data,scale.unit=FALSE,ncp,graph=F,quali.sup=1) + } + else + { + ## Suppression identifiants individus + data <- Tids[,-1] + verif_data() + + ## Analyse + res <- PCA(data,scale.unit=FALSE,ncp,graph=F) + } + + if (eigenplot==1) + { + par(mfrow=c(1,2)) + plot_ebouli(res,mt=mainTitle,cexc=textSize) + } + + if (contribplot==1) + { + par(mfrow=c(1,2)) + plot.contrib(res,mt=mainTitle,cexc=textSize) + } + + if (scoreplot==1) + { + if (hb==0) + { + par(mfrow=c(1,1)) + pca.indiv(res,hb=0,contribmin=minContribution,mt=mainTitle,cexc=textSize,plotax=principalPlane) + } + if (hb==1) + { + par(mfrow=c(1,1)) + pca.indiv(res,hb=1,facteur=facteur,contribmin=minContribution,mt=mainTitle,cexc=textSize,plotax=principalPlane) + } + } + if (loadingplot==1) + { + par(mfrow=c(1,1)) + pca.var(res,contribmin=minContribution,mt=mainTitle,cexc=textSize,plotax=principalPlane) + } + + if (eigenplot==1 || contribplot==1 || scoreplot==1 || loadingplot==1) + dev.off() + + + if (!is.null(res)){ + cat("<HTML><HEAD><TITLE>PCA FactoMineR report</TITLE></HEAD><BODY>\n",file=log_file,append=F,sep="") + cat("✓ Your process is successfull !<BR>",file=log_file,append=T,sep="") + cat("</BODY></HTML>\n",file=log_file,append=T,sep="") + + + + } +} + +###############################################################################################
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pcaFactoMineR_galaxy.R Thu Jan 18 07:57:36 2018 -0500 @@ -0,0 +1,137 @@ +#!/usr/local/bioinfo/bin/Rscript --vanilla --slave --no-site-file + +################################################################################################ +# pcaFactoMineR_galaxy # +# # +# Author : Sandrine Laguerre / Marie Tremblay-Franco / Jean-Francois Martin # +# User : Galaxy # +# Original data : -- # +# Starting date : 24-03-2015 # +# Version 1 : 20-05-2015 # +# Version 2 : 24-02-2016 # +# # +# # +# Input files : dataMatrix.txt # +# Output files : graph_output.pdf ; # +# # +################################################################################################ + +##------------------------------ +## Options +##------------------------------ +strAsFacL <- options()$stringsAsFactors +options(stringsAsFactors = FALSE) + +##------------------------------ +## Libraries laoding +##------------------------------ +# For parseCommandArgs function +library(batch) +library(pcaMethods) +library(FactoMineR) + +# R script call +source_local <- function(fname) +{ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + source(paste(base_dir, fname, sep="/")) +} + +#Import the different functions used for PCA + source_local("pcaFactoMineR_functions.R") + +##------------------------------ +## Constants +##------------------------------ +topEnvC <- environment() +flagC <- "\n" + + +##------------------------------ +## Lecture parametres +##------------------------------ +argLs <- parseCommandArgs(evaluate=FALSE) + +log_file <- argLs[["logOut"]] + # Inputs + # Matrice donnees +data <- read.table(argLs[["datafile"]],header=TRUE,sep="\t",dec=".",check.names = FALSE) +rownames(data) <- data[,1] + + # Facteur biologique +hb=0 +if(argLs[["factor"]] != "None") +{ + metadatasample <- read.table(argLs[["samplemetadata"]],header=TRUE,sep="\t",dec=".",check.names = FALSE) + rownames(metadatasample) <- metadatasample[,1] +# Test si le facteur choisi est bien dans le samplemetadata + if (any(argLs[["factor"]] %in% colnames(metadatasample)) ==FALSE) + { + #log_error(simpleCondition("Factor is not in samplemetadata.")) + cat("<HTML><HEAD><TITLE>PCA FactoMineR report</TITLE></HEAD><BODY>\n",file=log_file,append=F,sep="") + cat("⚠ An error occurred while trying to read your factor table.\n<BR>",file=log_file,append=T,sep="") + cat("Please check that:\n<BR>",file=log_file,append=T,sep="") + cat("<UL>\n",file=log_file,append=T,sep="") + cat(" <LI> you wrote the name of the column of the factor matrix corresponding to the qualitative variable </LI>\n",file=log_file,append=T,sep="") + cat(" <LI> you wrote the column name correctly (it is case sensitive)</LI>\n",file=log_file,append=T,sep="") + cat("</UL>\n",file=log_file,append=T,sep="") + cat("</BODY></HTML>\n",file=log_file,append=T,sep="") + q(save="no",status=1) + } +# On cree une dataframe avec l’id des samples (1ere colonne de metadatasample+ le facteur choisi +# qui est en colonne “colfactor†+ colfactor <- which(argLs[["factor"]] == colnames(metadatasample)) + facteur <- data.frame(metadatasample[,1], metadatasample[[colfactor]]) + facteur[[2]] <- as.factor(facteur[[2]]) + hb=1 +} + + # Appel de la fonction +eigenplot=0 +contribplot=0 +scoreplot=0 +loadingplot=0 +variable_in_line=0 + +if (argLs[["plotev"]]=="yes") +{ + eigenplot=1 +} + +if (argLs[["plotcontrib"]]=="yes") +{ + contribplot=1 +} + + +if (argLs[["plotindiv"]]=="yes") +{ + scoreplot=1 +} + + +if (argLs[["plotvar"]]=="yes") +{ + loadingplot=1 +} + +if (argLs[["varinline"]]=="yes") +{ + variable_in_line=1 +} + + + + + + # Outputs +nomGraphe <- argLs[["outgraphpdf"]] +res.pca <- pca.main(ids=data,bioFact=facteur,ncp=argLs[["npc"]],hb=hb, + minContribution=c(argLs[["contribh"]],argLs[["contribv"]]),mainTitle=argLs[["title"]], + textSize=argLs[["tc"]],principalPlane=c(argLs[["pch"]],argLs[["pcv"]]),eigenplot=eigenplot, + contribplot=contribplot,scoreplot=scoreplot,loadingplot=loadingplot, + nomGraphe=argLs[["outgraphpdf"]],variable_in_line=variable_in_line,log_file=log_file) + + +################################# fin ##############################################
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/decathlon.tsv Thu Jan 18 07:57:36 2018 -0500 @@ -0,0 +1,42 @@ +"name" "100m" "Long.jump" "Shot.put" "High.jump" "400m" "110m.hurdle" "Discus" "Pole.vault" "Javeline" "1500m" +"SEBRLE" 11.04 7.58 14.83 2.07 49.81 14.69 43.75 5.02 63.19 291.7 +"CLAY" 10.76 7.4 14.26 1.86 49.37 14.05 50.72 4.92 60.15 301.5 +"KARPOV" 11.02 7.3 14.77 2.04 48.37 14.09 48.95 4.92 50.31 300.2 +"BERNARD" 11.02 7.23 14.25 1.92 48.93 14.99 40.87 5.32 62.77 280.1 +"YURKOV" 11.34 7.09 15.19 2.1 50.42 15.31 46.26 4.72 63.44 276.4 +"WARNERS" 11.11 7.6 14.31 1.98 48.68 14.23 41.1 4.92 51.77 278.1 +"ZSIVOCZKY" 11.13 7.3 13.48 2.01 48.62 14.17 45.67 4.42 55.37 268 +"McMULLEN" 10.83 7.31 13.76 2.13 49.91 14.38 44.41 4.42 56.37 285.1 +"MARTINEAU" 11.64 6.81 14.57 1.95 50.14 14.93 47.6 4.92 52.33 262.1 +"HERNU" 11.37 7.56 14.41 1.86 51.1 15.06 44.99 4.82 57.19 285.1 +"BARRAS" 11.33 6.97 14.09 1.95 49.48 14.48 42.1 4.72 55.4 282 +"NOOL" 11.33 7.27 12.68 1.98 49.2 15.29 37.92 4.62 57.44 266.6 +"BOURGUIGNON" 11.36 6.8 13.46 1.86 51.16 15.67 40.49 5.02 54.68 291.7 +"Sebrle" 10.85 7.84 16.36 2.12 48.36 14.05 48.72 5 70.52 280.01 +"Clay" 10.44 7.96 15.23 2.06 49.19 14.13 50.11 4.9 69.71 282 +"Karpov" 10.5 7.81 15.93 2.09 46.81 13.97 51.65 4.6 55.54 278.11 +"Macey" 10.89 7.47 15.73 2.15 48.97 14.56 48.34 4.4 58.46 265.42 +"Warners" 10.62 7.74 14.48 1.97 47.97 14.01 43.73 4.9 55.39 278.05 +"Zsivoczky" 10.91 7.14 15.31 2.12 49.4 14.95 45.62 4.7 63.45 269.54 +"Hernu" 10.97 7.19 14.65 2.03 48.73 14.25 44.72 4.8 57.76 264.35 +"Nool" 10.8 7.53 14.26 1.88 48.81 14.8 42.05 5.4 61.33 276.33 +"Bernard" 10.69 7.48 14.8 2.12 49.13 14.17 44.75 4.4 55.27 276.31 +"Schwarzl" 10.98 7.49 14.01 1.94 49.76 14.25 42.43 5.1 56.32 273.56 +"Pogorelov" 10.95 7.31 15.1 2.06 50.79 14.21 44.6 5 53.45 287.63 +"Schoenbeck" 10.9 7.3 14.77 1.88 50.3 14.34 44.41 5 60.89 278.82 +"Barras" 11.14 6.99 14.91 1.94 49.41 14.37 44.83 4.6 64.55 267.09 +"Smith" 10.85 6.81 15.24 1.91 49.27 14.01 49.02 4.2 61.52 272.74 +"Averyanov" 10.55 7.34 14.44 1.94 49.72 14.39 39.88 4.8 54.51 271.02 +"Ojaniemi" 10.68 7.5 14.97 1.94 49.12 15.01 40.35 4.6 59.26 275.71 +"Smirnov" 10.89 7.07 13.88 1.94 49.11 14.77 42.47 4.7 60.88 263.31 +"Qi" 11.06 7.34 13.55 1.97 49.65 14.78 45.13 4.5 60.79 272.63 +"Drews" 10.87 7.38 13.07 1.88 48.51 14.01 40.11 5 51.53 274.21 +"Parkhomenko" 11.14 6.61 15.69 2.03 51.04 14.88 41.9 4.8 65.82 277.94 +"Terek" 10.92 6.94 15.15 1.94 49.56 15.12 45.62 5.3 50.62 290.36 +"Gomez" 11.08 7.26 14.57 1.85 48.61 14.41 40.95 4.4 60.71 269.7 +"Turi" 11.08 6.91 13.62 2.03 51.67 14.26 39.83 4.8 59.34 290.01 +"Lorenzo" 11.1 7.03 13.22 1.85 49.34 15.38 40.22 4.5 58.36 263.08 +"Karlivans" 11.33 7.26 13.3 1.97 50.54 14.98 43.34 4.5 52.92 278.67 +"Korkizoglou" 10.86 7.07 14.81 1.94 51.16 14.96 46.07 4.7 53.05 317 +"Uldal" 11.23 6.99 13.53 1.85 50.95 15.09 43.01 4.5 60 281.7 +"Casarsa" 11.36 6.68 14.92 1.94 53.2 15.39 48.66 4.4 58.62 296.12