# HG changeset patch # User proteomisc # Date 1701612368 0 # Node ID 09a8947f1031eda4358121a3b54bb0df430ced51 # Parent 9a7f56a398fa1a583bbeccc5a2d25b67cb2378bb Uploaded diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/Affymetrix.Rmd --- a/preprocess_datasets/Affymetrix.Rmd Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,373 +0,0 @@ - - - Preprocessing Plots Before and After - - - -
-

Preprocessing

-

-Preprocessing of an `r datasetsource` DataSet, issued from -`r technology` -technology. -

-

Used methods for each step

- -

Background correction methods

-
method : `r listArguments[["backgroundcorrection_method"]]`
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Normalization methods

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method : `r listArguments[["normalization_method"]]`
-

Summarization methods

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method : `r listArguments[["summary_method"]]`
-

Boxplots

-

Before NM

-

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-

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After NM

-

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- -
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-

MA plots

-

-
- -
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-

Densities plot

-

Before NM

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- -
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After NM

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- -
-

- - diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/Affymetrix_Preprocessing.R --- a/preprocess_datasets/Affymetrix_Preprocessing.R Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,93 +0,0 @@ -options(show.error.messages=F, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) -sink(stdout(), type = "message") -suppressWarnings(suppressMessages(library(affy))) -suppressWarnings(suppressMessages(library(affyPLM))) -suppressWarnings(suppressMessages(library(batch))) -suppressWarnings(suppressMessages(library(annotate))) -suppressWarnings(suppressMessages(library(limma))) -suppressWarnings(suppressMessages(library(markdown))) -suppressWarnings(suppressMessages(library(knitr))) -suppressWarnings(suppressMessages(library(BiocInstaller))) -source_local <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - source(paste(base_dir, fname, sep="/")) -} -file_path <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - pato <- paste(base_dir, fname, sep="/") - return(pato) -} -base_dir <- function(){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - return(base_dir) -} -source_local("Affymetrix_Preprocessing_Functions.R") -listArguments = parseCommandArgs(evaluate=FALSE) -thefunctions=listArguments[["thefunctions"]] -listArguments[["thefunctions"]]=NULL -h=listArguments[["h"]] -listArguments[["h"]]=NULL -w=listArguments[["w"]] -listArguments[["w"]]=NULL -if (!is.null(listArguments[["image"]])){ - load(listArguments[["image"]]) - listArguments[["image"]]=NULL -} -listArguments[["path"]]="" -print(listArguments) -listArguments[["rawdata"]]=MicroArray_Object$affy_object -if(datasetsource=="intern"){ -designo<-MicroArray_Object$designo -} - -if(datasetsource=="extern"){ -listArguments<-append(listArguments,list(datasetsource=datasetsource,listfullnames=listfullnames)) -} -Prepro_object<-do.call(thefunctions,listArguments) -if(datasetsource=="extern"){ -rownames(Prepro_object$data.bg@phenoData@data)<-listfullnames -colnames(exprs(Prepro_object$data.bg))<-listfullnames -colnames(exprs(Prepro_object$data.sm))<-listfullnames -colnames(exprs(Prepro_object$data.norm))<-listfullnames -colnames(exprs(Prepro_object$data.bg))<-listfullnames -colnames(exprs(Prepro_object$data.norm))<-listfullnames -rownames(Prepro_object$data.norm@phenoData@data)<-listfullnames -rownames(Prepro_object$data.norm@protocolData@data)<-listfullnames -} -par(las=2,mar=c(15,2,1,1)) -png(filename ="boxplot_before_NM.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -par(las=2,mar=c(15,2,1,1)) -boxplot((na.omit(as.data.frame(exprs(Prepro_object$data.bg)))), main="Boxplot of intensities before Normalization",col="red",las=2,mar=c(15,2,1,1)) - -dev.off() - - - -par(las=2,mar=c(15,2,1,1)) -png(filename ="boxplot_after_NM.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -par(las=2,mar=c(15,2,1,1)) -boxplot((na.omit(as.data.frame(exprs(Prepro_object$data.sm)))), main="Boxplot of intensities After Normalization",col="red",ylab="(intensities)",las=2,mar=c(15,2,1,1)) - -dev.off() -png(filename ="MA_plot.png",width = w, height = h) -MAplot((Prepro_object$data.norm) , - show.statistics = F, span = 2/3, family.loess = "gaussian", - cex = 2, plot.method = as.character("smoothScatter"), - azdd.loess = TRUE, lwd = 1, lty = 1, loess.col = "red") - -dev.off() -png(filename = "densities_plot_before_NM.png",width = w, height = h) -plotDensities(exprs(Prepro_object$data.bg),log=T) -dev.off() - -png(filename = "densities_plot_after_NM.png",width = w, height = h) -plotDensities(exprs(Prepro_object$data.norm),log=T) -dev.off() -AffymetrixRmd=file_path("Affymetrix.Rmd") -Style=file_path("look.css") -suppressWarnings(suppressMessages(knit2html(AffymetrixRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) -rm(listArguments) -save.image("MicroArray.Preprocessing.RData") diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/Affymetrix_Preprocessing_Functions.R --- a/preprocess_datasets/Affymetrix_Preprocessing_Functions.R Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,32 +0,0 @@ -AffymetrixPreprocessingFunction<-function(path="",rawdata,backgroundcorrection_method,normalization_method,summary_method,datasetsource="",listfullnames="") -{ - colnames(exprs(rawdata))<-listfullnames - data.bg<-bg.correct(rawdata, method=backgroundcorrection_method) - data.norm<-normalize(data.bg, method=normalization_method) - data.sm<-threestep(data.norm, background=F, normalize=F,summary.method=summary_method) - data_matrix=exprs(data.sm) - sampleNames(data.sm)<-listfullnames - if(datasetsource=="extern"){ - colnames(data_matrix)<-listfullnames - data.sm=ExpressionSet(data_matrix,phenoData=phenoData(data.sm),featureData=featureData(data.sm), - experimentData=experimentData(data.sm),annotation=annotation(data.sm),protocolData=protocolData(data.sm)) - write.table(format(exprs(data.sm), justify="right"),sep="\t", quote=FALSE, - row.names=T, col.names=T,file="Matrix.Data.tsv") - }else{ - colnames(data_matrix)<-designo$sample - data.sm=ExpressionSet(data_matrix,phenoData=phenoData(data.sm),featureData=featureData(data.sm), - experimentData=experimentData(data.sm),annotation=annotation(data.sm),protocolData=protocolData(data.sm)) - write.table(format(exprs(data.sm), justify="right"),sep="\t", quote=FALSE, - row.names=T, col.names=T,file="Matrix.Data.tsv") - } - installed<-as.data.frame(installed.packages()) - lbraries=paste(annotation(data.sm),"db",sep='.') - if(!lbraries%in%installed$Package){ - biocLite(lbraries[!lbraries%in%installed$Package])} - - suppressWarnings(suppressMessages(library(lbraries,character.only = TRUE))) - - symbol<-getSYMBOL(rownames(exprs(data.sm)), annotation(data.sm)) - return(list(data.bg=data.bg,data.norm=data.norm,data.sm=data.sm,matrix_data=exprs(data.sm),symbol=symbol)) - - } diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/Agilent_One_Color_Preprocessing.R --- a/preprocess_datasets/Agilent_One_Color_Preprocessing.R Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,89 +0,0 @@ -options(show.error.messages=F, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) -sink(stdout(), type = "message") -suppressWarnings(suppressMessages(library(limma))) -suppressWarnings(suppressMessages(library(batch))) -suppressWarnings(suppressMessages(library(marray))) -suppressWarnings(suppressMessages(library(IDPmisc))) -suppressWarnings(suppressMessages(library(markdown))) -suppressWarnings(suppressMessages(library(knitr))) -source_local <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - source(paste(base_dir, fname, sep="/")) -} -file_path <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - pato <- paste(base_dir, fname, sep="/") - return(pato) -} -base_dir <- function(){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - return(base_dir) -} -source_local("Agilent_One_Color_Preprocessing_Functions.R") -listArguments = parseCommandArgs(evaluate=FALSE) -print(listArguments) -load(listArguments[["image"]]) -names(listArguments)[which(names(listArguments)=="image")]="data" -listArguments[["data"]]=MicroArray_Object$RFile -if(datasetsource=="intern"){ -designo<-MicroArray_Object$designo -} -thefunction=listArguments[["thefunction"]] -listArguments[["thefunction"]]=NULL -listArguments[["thefunctions"]]=NULL -h=listArguments[["h"]] -listArguments[["h"]]=NULL -w=listArguments[["w"]] -listArguments[["w"]]=NULL -Prepro_object<-do.call(thefunction,listArguments) -if(datasetsource=="extern"){ -colnames(MicroArray_Object[[1]]$E)<-listfullnames -colnames(Prepro_object$dataBG$E)<-listfullnames -colnames(Prepro_object$dataNBA$E)<-listfullnames -colnames(MicroArray_Object[[1]]@.Data[[1]])<-listcelsnames[-1] -colnames(MicroArray_Object[[1]]@.Data[[2]])<-listcelsnames[-1] -rownames(MicroArray_Object[[1]]@.Data[[3]])<-listcelsnames[-1] -MicroArray_Object[[1]]@.Data[[3]]$FileName<-listfullnames -colnames(Prepro_object$dataBG@.Data[[1]])<-listcelsnames[-1] -Prepro_object$dataBG@.Data[[2]]$FileName<-listfullnames -colnames(Prepro_object$dataNBA[[1]])<-listcelsnames[-1] -Prepro_object$dataNBA[[2]]$FileName<-listfullnames -} -par(las=2,mar=c(15,2,1,1)) -png(filename ="boxplot_before_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$E))), main="Boxplot of log2( intensities) before Background Correction",col="red",ylab="log2( intensities)",xlab="",las=2,mar=c(15,2,1,1)) - -dev.off() - -png(filename ="boxplot_after_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") - -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$E))), main="Boxplot of log2( intensities) After Background Correction",col="red",ylab="log2( intensities)",xlab="",las=2,mar=c(15,2,1,1)) - -dev.off() - - -png(filename ="boxplot_after_NBA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") - -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNBA$E))), main="Boxplot of log2( intensities) After Normalization Between Arrays",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) - -dev.off() -png(filename = "densities_plot_before_BG.png",width = w, height = h) -plotDensities(MicroArray_Object[[1]],log=T) -dev.off() - -png(filename = "densities_plot_after_BG.png",width = w, height = h) -plotDensities(Prepro_object$dataBG,log=T) -dev.off() - - -png(filename = "densities_plot_after_NBA.png",width = w, height = h) -plotDensities(Prepro_object$dataNBA,log=T) -dev.off() -OneColorRmd=file_path("OneColor.Rmd") -Style=file_path("look.css") -suppressWarnings(suppressMessages(knit2html(OneColorRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) -rm(listArguments) -save.image("MicroArray.Preprocessing.RData") diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/Agilent_One_Color_Preprocessing_Functions.R --- a/preprocess_datasets/Agilent_One_Color_Preprocessing_Functions.R Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,17 +0,0 @@ -AgilentOneColorPreprocessingFunction<- function(path,data,methodBC,methodNBA) -{ -MA <<- backgroundCorrect(data, method=methodBC ,offset = 2) -rownames(MA$E)=MA$genes$ProbeName -MA<-MA[rm.na(rownames(MA$E)),] -MAb <<-suppressWarnings(suppressMessages(normalizeBetweenArrays(MA, method=methodNBA))) -data_mt<-NaRV.omit(as.data.frame(MAb$E)) -MAb$E=(data_mt) -MAb$genes=(MAb$genes[(MAb$genes$ProbeName %in% rownames(MAb$E)),]) -MA.avg <-suppressWarnings(suppressMessages(avereps(MAb, ID=MAb$genes$ProbeName))) -data_matrix=NaRV.omit(MA.avg$E) -colnames(data_matrix)<-designo$sample -write.table(format(data_matrix, justify="right"),sep="\t", quote=FALSE, - row.names=T, col.names=T,file="Matrix.Data.tsv") - -return(list(dataNBA=MA.avg,dataBG=MA,matrix_data=as.matrix(MA.avg$E),symbol=MA.avg$genes$GeneName)) -} diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/Agilent_Two_Colors_Preprocessing.R --- a/preprocess_datasets/Agilent_Two_Colors_Preprocessing.R Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,113 +0,0 @@ -options(show.error.messages=F, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) -sink(stdout(), type = "message") -suppressWarnings(suppressMessages(library(limma))) -suppressWarnings(suppressMessages(library(batch))) -suppressWarnings(suppressMessages(library(marray))) -suppressWarnings(suppressMessages(library(IDPmisc))) -suppressWarnings(suppressMessages(library(affy))) -suppressWarnings(suppressMessages(library(markdown))) -suppressWarnings(suppressMessages(library(knitr))) -source_local <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - source(paste(base_dir, fname, sep="/")) -} -file_path <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - pato <- paste(base_dir, fname, sep="/") - return(pato) -} -base_dir <- function(){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - return(base_dir) -} -source_local("Make_matrix_two_channels.R") -source_local("Agilent_Two_Colors_Preprocessing_Functions.R") -listArguments = parseCommandArgs(evaluate=FALSE) -print(listArguments) -# print(thefunction) -load(listArguments[["image"]]) -names(listArguments)[which(names(listArguments)=="image")]="data" -listArguments[["data"]]=MicroArray_Object$RFile - -thefunction=listArguments[["thefunction"]] -listArguments[["thefunction"]]=NULL -h=listArguments[["h"]] -listArguments[["h"]]=NULL -w=listArguments[["w"]] -listArguments[["w"]]=NULL -# print(thefunction) -if(datasetsource=="intern"){ -designo<-MicroArray_Object$designo -} - -Prepro_object<-do.call(thefunction,listArguments) -designo<-Prepro_object$designo -RGNBA=RG.MA(Prepro_object$dataNBA) -if(datasetsource=="extern"){ -colnames(MicroArray_Object[[1]]$G)<-listcelsnames[-1] -colnames(MicroArray_Object[[1]]$R)<-listcelsnames[-1] -colnames(Prepro_object$dataBG$G)<-listcelsnames[-1] -colnames(Prepro_object$dataBG$R)<-listcelsnames[-1] -colnames(Prepro_object$dataNWA$G)<-listcelsnames[-1] -colnames(Prepro_object$dataNWA$R)<-listcelsnames[-1] -colnames(RGNBA$G)<-listcelsnames[-1] -colnames(RGNBA$R)<-listcelsnames[-1] - -} -par(las=2,mar=c(15,2,1,1)) -png(filename ="boxplot_before_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$R))), main="Boxplot of log2(R intensities) before BGC",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) -boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$G))), main="Boxplot of log2(G intensities) before BGC",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -dev.off() - -png(filename ="boxplot_after_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$R))), main="Boxplot of log2(R intensities) After BGC",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$G))), main="Boxplot of log2(G intensities) After BGC",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -dev.off() - -png(filename ="boxplot_after_NWA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNWA$R))), main="Boxplot of log2(R intensities) After NWA",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNWA$G))), main="Boxplot of log2(G intensities) After NWA",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -dev.off() -png(filename ="boxplot_after_NBA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(RGNBA$R))), main="Boxplot of log2(R intensities) After NBA",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) -boxplot(log2(na.omit(as.data.frame(RGNBA$G))), main="Boxplot of log2(G intensities) After NBA",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -dev.off() -png(filename ="MA_plot.png",width = w, height = h) -ma.plot(na.omit(Prepro_object$dataNBA$A), na.omit(Prepro_object$dataNBA$M), - show.statistics = F, span = 2/3, family.loess = "gaussian", - cex = 2, plot.method = as.character("smoothScatter"), - add.loess = TRUE, lwd = 1, lty = 1, loess.col = "red",main="MA plot") - -dev.off() -png(filename = "densities_plot_before_BG.png",width = w, height = h) -plotDensities(MicroArray_Object[[1]],log=T) -dev.off() - -png(filename = "densities_plot_after_BG.png",width = w, height = h) -plotDensities(Prepro_object$dataBG,log=T) -dev.off() - -png(filename = "densities_plot_after_NWA.png",width = w, height = h) -plotDensities(Prepro_object$dataNWA,log=T) -dev.off() - -png(filename = "densities_plot_after_NBA.png",width = w, height = h) -plotDensities(Prepro_object$dataNBA,log=T) -dev.off() -TwoColorsRmd=file_path("TwoColors.Rmd") -Style=file_path("look.css") -suppressWarnings(suppressMessages(knit2html(TwoColorsRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) -rm(listArguments) -save.image("MicroArray.Preprocessing.RData") diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/Agilent_Two_Colors_Preprocessing_Functions.R --- a/preprocess_datasets/Agilent_Two_Colors_Preprocessing_Functions.R Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,21 +0,0 @@ -AgilentTwoChannelsPreprocessingFunction<- function(path,data,methodBC,methodNWA,methodNBA) -{ - RG <<- suppressWarnings(suppressMessages(backgroundCorrect(data,method=methodBC, offset= 16))) - MA <<- suppressWarnings(suppressMessages(normalizeWithinArrays(RG, method=methodNWA,bc.method="none"))) - rownames(MA$A)=rownames(MA$M)=MA$gene$ProbeName - MA<-MA[rm.na(rownames(MA$M)),] - MAb <<- suppressWarnings(suppressMessages(normalizeBetweenArrays(MA, method=methodNBA))) - data_mt<-NaRV.omit(as.data.frame(MAb$M)) - MAb$M=(data_mt) - MAb$A=NaRV.omit(as.data.frame(MAb$A)) - MAb$genes=(MAb$genes[(MAb$genes$ProbeName %in% c(rownames(MAb$A),rownames(MAb$M))),]) - RG.pq <<- RG.MA(MA) - MA.avg <- suppressWarnings(suppressMessages(avereps(MAb,ID=MAb$genes$ProbeName))) - data_matrix=NaRV.omit(MA.avg$M) - colnames(data_matrix)<-designo$sample - write.table(format(data_matrix, justify="right"),sep="\t", quote=FALSE, - row.names=T, col.names=T,file="Matrix.Data.tsv") - Prepro_object1<-list(dataBG=RG,dataNWA=RG.pq,dataNBA=MA.avg,matrix_data=as.matrix(data_matrix),symbol=(MA.avg$genes$GeneName)) - Prepro_object1=make_design(MA_matrix=Prepro_object1) - return(Prepro_object1) -} diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/GenePix_One_Color_Preprocessing.R --- a/preprocess_datasets/GenePix_One_Color_Preprocessing.R Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,91 +0,0 @@ -options(show.error.messages=F, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) -sink(stdout(), type = "message") -suppressWarnings(suppressMessages(library(limma))) -suppressWarnings(suppressMessages(library(marray))) -suppressWarnings(suppressMessages(library(batch))) -suppressWarnings(suppressMessages(library(IDPmisc))) -suppressWarnings(suppressMessages(library(markdown))) -suppressWarnings(suppressMessages(library(knitr))) -source_local <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - source(paste(base_dir, fname, sep="/")) -} -file_path <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - pato <- paste(base_dir, fname, sep="/") - return(pato) -} -base_dir <- function(){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - return(base_dir) -} -source_local("GenePix_One_Color_Preprocessing_Functions.R") -listArguments = parseCommandArgs(evaluate=FALSE) -print(listArguments) -load(listArguments[["image"]]) -names(listArguments)[which(names(listArguments)=="image")]="data" -listArguments[["data"]]=MicroArray_Object$RFile -if(datasetsource=="intern"){ -designo<-MicroArray_Object$designo -} -thefunction=listArguments[["thefunction"]] -listArguments[["thefunction"]]=NULL -listArguments[["thefunctions"]]=NULL -h=listArguments[["h"]] -listArguments[["h"]]=NULL -w=listArguments[["w"]] -listArguments[["w"]]=NULL -Prepro_object<-do.call(thefunction,listArguments) -RGNBA=RG.MA(Prepro_object$dataNBA) -if(datasetsource=="extern"){ -colnames(MicroArray_Object[[1]]$E)<-listfullnames# -colnames(Prepro_object$dataBG$E)<-listfullnames# -colnames(Prepro_object$dataNBA$E)<-listfullnames# -colnames(MicroArray_Object[[1]]@.Data[[1]])<-listcelsnames[-1]# -colnames(MicroArray_Object[[1]]@.Data[[2]])<-listcelsnames[-1]# -rownames(MicroArray_Object[[1]]@.Data[[3]])<-listcelsnames[-1]# -MicroArray_Object[[1]]@.Data[[3]]$FileName<-listfullnames# -colnames(Prepro_object$dataBG@.Data[[1]])<-listcelsnames[-1]# -Prepro_object$dataBG@.Data[[2]]$FileName<-listfullnames# -colnames(Prepro_object$dataNBA[[1]])<-listcelsnames[-1]# -Prepro_object$dataNBA[[2]]$FileName<-listfullnames# -} -par(las=2,mar=c(15,2,1,1)) -png(filename ="boxplot_before_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") - -boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$E))), main="Boxplot of log2( intensities) before Background Correction",col="red",ylab="log2( intensities)",xlab="",las=2,mar=c(15,2,1,1)) - -dev.off() - -png(filename ="boxplot_after_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") - -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$E))), main="Boxplot of log2( intensities) After Background Correction",col="red",ylab="log2( intensities)",xlab="",las=2,mar=c(15,2,1,1)) - -dev.off() - - -png(filename ="boxplot_after_NBA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") - -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNBA$E))), main="Boxplot of log2( intensities) After Normalization Between Arrays",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) - -dev.off() -png(filename = "densities_plot_before_BG.png",width = w, height = h) -plotDensities(MicroArray_Object[[1]],log=T) -dev.off() - -png(filename = "densities_plot_after_BG.png",width = w, height = h) -plotDensities(Prepro_object$dataBG,log=T) -dev.off() - - -png(filename = "densities_plot_after_NBA.png",width = w, height = h) -plotDensities(Prepro_object$dataNBA,log=T) -dev.off() -OneColorRmd=file_path("OneColor.Rmd") -Style=file_path("look.css") -suppressWarnings(suppressMessages(knit2html(OneColorRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) -rm(listArguments) -save.image("MicroArray.Preprocessing.RData") diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/GenePix_One_Color_Preprocessing_Functions.R --- a/preprocess_datasets/GenePix_One_Color_Preprocessing_Functions.R Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,17 +0,0 @@ -GenePixOneColorPreprocessingFunction<- function(path,data,methodBC,methodNBA) -{ - MA <<- suppressWarnings(suppressMessages(backgroundCorrect(data, method=methodBC ,offset = 16))) - rownames(MA$E)=MA$genes$ID - MA<-MA[rm.na(rownames(MA$E)),] - MAb <<-suppressWarnings(suppressMessages(normalizeBetweenArrays(MA, method=methodNBA))) - data_mt<-NaRV.omit(as.data.frame(MAb$E)) - MAb$E=(data_mt) - MAb$genes=(MAb$genes[(MAb$genes$ID %in% rownames(MAb$E)),]) - MA.avg <-suppressWarnings(suppressMessages(avereps(MAb, ID=MAb$genes$ID))) - data_matrix=NaRV.omit(MA.avg$E) - colnames(data_matrix)<-designo$sample - write.table(format(data_matrix, justify="right"),sep="\t", quote=FALSE, - row.names=T, col.names=T,file="Matrix.Data.tsv") - return(list(dataNBA=MA.avg,dataBG=MA,matrix_data=as.matrix(MA.avg$E),symbol=MA.avg$genes$Name)) -} - diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/GenePix_Two_Colors_Preprocessing.R --- a/preprocess_datasets/GenePix_Two_Colors_Preprocessing.R Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,110 +0,0 @@ -options(show.error.messages=F, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) -sink(stdout(), type = "message") -suppressWarnings(suppressMessages(library(limma))) -suppressWarnings(suppressMessages(library(marray))) -suppressWarnings(suppressMessages(library(batch))) -suppressWarnings(suppressMessages(library(IDPmisc))) -suppressWarnings(suppressMessages(library(affy))) -suppressWarnings(suppressMessages(library(markdown))) -suppressWarnings(suppressMessages(library(knitr))) -source_local <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - source(paste(base_dir, fname, sep="/")) -} -file_path <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - pato <- paste(base_dir, fname, sep="/") - return(pato) -} -base_dir <- function(){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - return(base_dir) -} -source_local("Make_matrix_two_channels.R") -source_local("GenePix_Two_Colors_Preprocessing_Functions.R") -listArguments = parseCommandArgs(evaluate=FALSE) -print(listArguments) -load(listArguments[["image"]]) -names(listArguments)[which(names(listArguments)=="image")]="data" -listArguments[["data"]]=MicroArray_Object$RFile -thefunction=listArguments[["thefunction"]] -listArguments[["thefunction"]]=NULL -h=listArguments[["h"]] -listArguments[["h"]]=NULL -w=listArguments[["w"]] -listArguments[["w"]]=NULL -# print(thefunction) -if(datasetsource=="intern"){ -designo<-MicroArray_Object$designo -} -Prepro_object<-do.call(thefunction,listArguments) -designo<-Prepro_object$designo -RGNBA=RG.MA(Prepro_object$dataNBA) -if(datasetsource=="extern"){ -colnames(MicroArray_Object[[1]]$G)<-listcelsnames[-1] -colnames(MicroArray_Object[[1]]$R)<-listcelsnames[-1] -colnames(Prepro_object$dataBG$G)<-listcelsnames[-1] -colnames(Prepro_object$dataBG$R)<-listcelsnames[-1] -colnames(Prepro_object$dataNWA$G)<-listcelsnames[-1] -colnames(Prepro_object$dataNWA$R)<-listcelsnames[-1] -colnames(RGNBA$G)<-listcelsnames[-1] -colnames(RGNBA$R)<-listcelsnames[-1] - -} -par(las=2,mar=c(15,2,1,1)) -png(filename ="boxplot_before_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$R))), main="Boxplot of log2(R intensities) before BGC",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) -boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$G))), main="Boxplot of log2(G intensities) before BGC",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -dev.off() - -png(filename ="boxplot_after_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$R))), main="Boxplot of log2(R intensities) After BGC",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$G))), main="Boxplot of log2(G intensities) After BGC",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -dev.off() - -png(filename ="boxplot_after_NWA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNWA$R))), main="Boxplot of log2(R intensities) After NWA",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNWA$G))), main="Boxplot of log2(G intensities) After NWA",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -dev.off() -png(filename ="boxplot_after_NBA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(RGNBA$R))), main="Boxplot of log2(R intensities) After NBA",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) -boxplot(log2(na.omit(as.data.frame(RGNBA$G))), main="Boxplot of log2(G intensities) After NBA",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -dev.off() -png(filename ="MA_plot.png",width = w, height = h) -ma.plot(na.omit(Prepro_object$dataNBA$A), na.omit(Prepro_object$dataNBA$M), - show.statistics = F, span = 2/3, family.loess = "gaussian", - cex = 2, plot.method = as.character("smoothScatter"), - add.loess = TRUE, lwd = 1, lty = 1, loess.col = "red",main="MA plot") - -dev.off() -png(filename = "densities_plot_before_BG.png",width = w, height = h) -plotDensities(MicroArray_Object[[1]],log=T) -dev.off() - -png(filename = "densities_plot_after_BG.png",width = w, height = h) -plotDensities(Prepro_object$dataBG,log=T) -dev.off() - -png(filename = "densities_plot_after_NWA.png",width = w, height = h) -plotDensities(Prepro_object$dataNWA,log=T) -dev.off() - -png(filename = "densities_plot_after_NBA.png",width = w, height = h) -plotDensities(Prepro_object$dataNBA,log=T) -dev.off() -TwoColorsRmd=file_path("TwoColors.Rmd") -Style=file_path("look.css") -suppressWarnings(suppressMessages(knit2html(TwoColorsRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) -rm(listArguments) -save.image(file="MicroArray.Preprocessing.RData") diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/GenePix_Two_Colors_Preprocessing_Functions.R --- a/preprocess_datasets/GenePix_Two_Colors_Preprocessing_Functions.R Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,21 +0,0 @@ -GenePixTwoChannelsPreprocessingFunction<- function(path,data,methodBC,methodNWA,methodNBA) -{ - RG <<- backgroundCorrect(data,method=methodBC, offset=64) - MA <<- suppressWarnings(suppressMessages(normalizeWithinArrays(RG, method=methodNWA,bc.method="none"))) - rownames(MA$A)=rownames(MA$M)=MA$gene$ID - MA<-MA[rm.na(rownames(MA$M)),] - RG.pq <<- RG.MA(MA) - MAb <<-suppressWarnings(suppressMessages(normalizeBetweenArrays(MA, method=methodNBA))) - data_mt<-NaRV.omit(as.data.frame(MAb$M)) - MAb$M=(data_mt) - MAb$A=NaRV.omit(as.data.frame(MAb$A)) - MAb$genes=(MAb$genes[(MAb$genes$ID %in% c(rownames(MAb$A),rownames(MAb$M))),]) - MA.avg <-suppressWarnings(suppressMessages(avereps(MAb, ID=MAb$genes$ID))) - data_matrix=NaRV.omit(MA.avg$M) - colnames(data_matrix)<-designo$sample - write.table(format(data_matrix, justify="right"),sep="\t", quote=FALSE, - row.names=T, col.names=T,file="Matrix.Data.tsv") - -return(make_design(MA_matrix=list(dataBG=RG,dataNWA=RG.pq,dataNBA=MA.avg,matrix_data=as.matrix(data_matrix),symbol=MA.avg$genes$Name))) -} - diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/Make_matrix_two_channels.R --- a/preprocess_datasets/Make_matrix_two_channels.R Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,28 +0,0 @@ -make_design<-function(MA_matrix){ - matrix<-RG.MA(MA_matrix$dataNBA) - colnames_matrix<-NULL - tmp<-strsplit(colnames(MA_matrix$dataNBA),split=".",fixed = T) - for(i in 1:ncol(MA_matrix$dataNBA)){ - colnames_matrix[i]<-paste(tmp[[i]][1],"R",sep=".") - - # .Red intensity - } - i=1; - for(j in (ncol(MA_matrix$dataNBA)+1):((ncol(MA_matrix$dataNBA)*2))){ - - colnames_matrix[j]<-paste(tmp[[i]][1],"G",sep=".") - i<-i+1; - # .Green intensity - } - matrix_data<-cbind(matrix$R,matrix$G) - colnames(matrix_data)<-colnames_matrix - rownames(matrix_data)<-rownames(MA_matrix$dataNBA) - MA_matrix$matrix_data<-log2(matrix_data) - groupe<-c(rep("case",ncol(matrix$R)),rep("control",ncol(matrix$G))) - sample=colnames(matrix_data) - designo<-data.frame(sample=sample,groupetype=rep(designo$group,2),group=groupe) - MA_matrix$designo<-designo - write.table(format(designo, justify="right"),sep="\t", quote=FALSE, - row.names=T, col.names=T,file="design.txt") - return(MA_matrix) -} diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/OneColor.Rmd --- a/preprocess_datasets/OneColor.Rmd Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,370 +0,0 @@ - - - Preprocessing Plots Before and After - - - -
-

Preprocessing

-

-Preprocessing of an `r datasetsource` DataSet, issued from -`r technology` -technology. -

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Used methods for each step

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Background correction methods

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method : `r listArguments[["methodBC"]]`
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method : `r listArguments[["methodNBA"]]`
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- - diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/Preprocess_DataSet.xml --- a/preprocess_datasets/Preprocess_DataSet.xml Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,306 +0,0 @@ - - Preprocessing microarrays datasets.Contains Background Correction, Normalization within arrays, between arrays (depending on the number of channels) and summarization. - - citations.xml - - - r-base - r-batch - bioconductor-affyplm - bioconductor-affy - bioconductor-annotate - r-knitr - bioconductor-marray - r-idpmisc - r-kernsmooth - r-rmarkdown - r-markdown - bioconductor-limma - r-idpmisc - - - - - - - - - - 'Read.Project' in value.name - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -.. class:: infomark - -**Authors** T.Bensellak, B.Ettetuani. - ---------------------------------------------------- - -================================== -Preprocessing Microarray DataSet -================================== - ------------ -Description ------------ - -This tool is used as first phase of the global workflow, the preprocessing . - ------------------ -Workflow position ------------------ - -**Upstream tools** - -+-------------------------------+------------------------------+---------+ -| Name | output file |format | -+===============================+==============================+=========+ -| Read.DataSet.Microarray | MicroArrayObject.RData | Rdat | -+-------------------------------+------------------------------+---------+ - - -**Downstream tools** - -+-----------------------------------------------+----------------------------------------------+---------+ -| Name | Output file | Format | -+===============================================+==============================================+=========+ -|Tests and Selection | Test.results.tsv | Tabular | -+-----------------------------------------------+----------------------------------------------+---------+ - ------------ -Input files ------------ - -+---------------------------+------------+ -| Parameter : num + label | Format | -+===========================+============+ -| Image | Rdata | -+---------------------------+------------+ -| Methods parmeters | Numeric | -+---------------------------+------------+ - ------------- -Output files ------------- - -**Microarray.Preprocessing.RData** - -**Matrix.Data.tsv** - ------------------------------- -General schema of the workflow ------------------------------- - -https://bensellak.github.io/microarrays-galaxy/workflow.png - - - - - - diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/TwoColors.Rmd --- a/preprocess_datasets/TwoColors.Rmd Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,387 +0,0 @@ - - - Preprocessing Plots Before and After - - - -
-

Preprocessing

-

-Preprocessing of an `r datasetsource` DataSet, issued from -`r technology` -technology. -

-

Used methods for each step

- -

Background correction methods

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method : `r listArguments[["methodBC"]]`
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Normalization methods

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methodNWA : `r listArguments[["methodNWA"]]`
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methodNBA : `r listArguments[["methodNBA"]]`
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- - diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/citations.xml --- a/preprocess_datasets/citations.xml Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,113 +0,0 @@ - - 1.0 - - - - @Manual{, - title = {R: A Language and Environment for Statistical Computing}, - author = {{R Core Team}}, - organization = {R Foundation for Statistical Computing}, - address = {Vienna, Austria}, - year = {2017}, - url = {https://www.R-project.org/}, - } - - - @Article{, - title = {Passing in Command Line Arguments and Parallel Cluster/Multicore Batching in {R} with {batch}}, - author = {Thomas J. Hoffmann}, - journal = {Journal of Statistical Software, Code Snippets}, - year = {2011}, - volume = {39}, - number = {1}, - pages = {1--11}, - url = {http://www.jstatsoft.org/v39/c01/}, - } - - - @Article{, - author = {Laurent Gautier and Leslie Cope and Benjamin M. Bolstad and Rafael A. Irizarry}, - title = {affy---analysis of Affymetrix GeneChip data at the probe level}, - journal = {Bioinformatics}, - volume = {20}, - number = {3}, - year = {2004}, - issn = {1367-4803}, - pages = {307--315}, - doi = {10.1093/bioinformatics/btg405}, - publisher = {Oxford University Press}, - address = {Oxford, UK}, - } - - - @Article{, - author = {Matthew E Ritchie and Belinda Phipson and Di Wu and Yifang Hu and Charity W Law and Wei Shi and Gordon K Smyth}, - title = {{limma} powers differential expression analyses for {RNA}-sequencing and microarray studies}, - journal = {Nucleic Acids Research}, - year = {2015}, - volume = {43}, - number = {7}, - pages = {e47}, - } - - - @Article{, - title = {Quality assessment for short oligonucleotide arrays.}, - author = {Julia Brettschneider and Francois Collin and Benjamin M Bolstad and Terence P Speed}, - journal = {Technometrics}, - year = {2007}, - volume = {In press}, - } - - - @Manual{, - title = {annotate: Annotation for microarrays}, - author = {R. Gentleman}, - year = {2017}, - note = {R package version 1.56.0}, - } - - - @Manual{, - title = {knitr: A General-Purpose Package for Dynamic Report Generation in R}, - author = {Yihui Xie}, - year = {2017}, - note = {R package version 1.16}, - url = {http://yihui.name/knitr/}, - } - - - @Manual{, - title = {marray: Exploratory analysis for two-color spotted microarray data}, - author = {Yee Hwa Yang with contributions from Agnes Paquet and Sandrine Dudoit.}, - year = {2009}, - note = {R package version 1.58.0}, - url = {http://www.maths.usyd.edu.au/u/jeany/}, - } - - - @Manual{, - title = {IDPmisc: Utilities of Institute of Data Analyses and Process Design -(www.idp.zhaw.ch)}, - author = {Rene Locher and Andreas Ruckstuhl et al.}, - year = {2012}, - note = {R package version 1.1.17}, - url = {https://CRAN.R-project.org/package=IDPmisc}, - } - - - @Manual{, - title = {KernSmooth: Functions for Kernel Smoothing Supporting Wand and Jones (1995)}, - author = {Matt Wand}, - year = {2015}, - note = {R package version 2.23-15}, - url = {https://CRAN.R-project.org/package=KernSmooth}, - } - - - - - - - - diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/look.css --- a/preprocess_datasets/look.css Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,317 +0,0 @@ -/* css racine */ - -body { -/* font-family: Comic Sans MS;*/ -} - -div.research { - background-color: #33ffff; /*#208090 */ /*#228491*/; - color: #0000ff; /* ffffff */ -} - -div.ensg { - background-color: #bbee00; - color: #0000ff; -} - -div.research span.invisible { - visibility:hidden; -} - -kbd { - color: #000000; -} - -pre { - color: #000000; -} - -A:link { - color: #0000ee; /*#ffffff;*/ -} - -A:active { - color: #ff0000; /* #ffffff */ -} - -A:hover { -/* font-size: 2em; */ - text-decoration: none; - color: #0000ee; /* ffffff */ - background-color: #FFFF33; -} - -h3 { - color: #FF0000; -} - -h4 { - color: #FF0000; -} - -div.correction { - color: #008800; -/* color: #000000; */ -} - -div.detail { - font-size: 70%; -} - -div.section { - text-align: center; - font-size: 140%; - color: #FF0000; -} - -div.subsection { - text-align: left; - font-size: 120%; - color: #bb0000; - background-color: #FFFF33; -} - -div.titreDuModule { - text-align: center; - font-size: 200%; - color: #FF0099; -} - -div.formation { - text-align: center; - font-size: 120%; - color: #FF0099; -} - -div.ensg.titreDuModule { - text-align: center; - font-size: 200%; - color: #FF0099; -} - -div.ensg.formation { - text-align: center; - font-size: 120%; - color: #FF0099; -} - -span.indice { - font-size: 70%; -} - -span.question { - color: #bb0000; -} - -span.tresImportant { - color: #bb0000; - font-size: 200% -} - -span.assezImportant { - color: #bb0000; - font-size: 150% -} - -span.important { - color: #bb0000; -} - -span.crucial { - color: #bb0000; -} - -span.crucial:hover { - font-size: 400%; -} - -acronym { - text-decoration: none; -} - -div.theoreme:before { - content: "Théorème : "; -} - -div.theoreme:after { - content: "emèroéhT"; -} - -div.theoreme ul li:before { - content: "1 alinéa "; -} - -div.theoreme li:after { - content: " ce qui termine l'alinéa"; -} - -div.tpID { - background-color: #33ffff; - color: #0000ff; -} - -div.tpR { - font-family: serif; - color: #000000; - background-color: #fff; -} - -div.tpR span.detail { - font-size: 75%; -} - -div.tpR div.correction:before { - content: "Idée de la correction : "; -} - -div.tpR div.correction { - background-color: #00ffff; - border: solid #009999; - padding: 0.5em; - margin-left: 2em; - border-width: 1px; -} - -div.tpR div.exercices:before { - content: "Exercices : "; -} -div.tpR div.exercices { - background-color: #00ee00; - border: solid #00cc00; - padding: 0.5em; - margin-left: 2em; - border-width: 1px; -} - -div.tpR div.solution:before { - content: "Solution : "; -} -div.tpR div.solution { - background-color: #ff00ff; - border: solid #990099; - padding: 0.5em; - margin-left: 2em; - border-width: 1px; -} - -div.tpR div.exercice:before { - content: "Exercice : "; -} -div.tpR div.exercice { - background-color: #00ee00; - border: solid #00cc00; - padding: 0.5em; - margin-left: 2em; - border-width: 1px; -} - -div.tpR div.questions:before { - content: "Questions : "; -} -div.tpR div.questions { - background-color: #ff99ff; - border: solid #ff99ff; - padding: 0.5em; - margin-left: 2em; - border-width: 1px; -} - -div.tpR span.index { -/* background-color: #ffff33;*/ -} - -div.tpR h1 { - font-family: sans-serif; - color: #000; - border-style: solid; - background-color: #ddf; - border-color: #88f; - border-width: 1px; - padding-left: 0.5em; -} - -div.tpR h2 { - font-family: sans-serif; - color: #000; - border-style: solid; - border-color: #8f8; - background-color: #dfd; - border-width: 1px; - padding-left: 0.5em; -} - -div.tpR h3 { - font-family: sans-serif; - color: #000; - border-style: solid; - background-color: #fdd; - border-color: #f88; - border-width: 1px; - padding-left: 0.5em; -} - -div.tpR a:link { - color: #00f -} - -div.tpR a:visited { - color: #f0f -} - -div.tpR p { - margin-left: 1em; -} - -div.tpR pre { - background-color: #eee; - border: solid #ccc; - padding: 0.5em; - margin-left: 2em; - border-width: 1px; -} - -.redify pre { - color: #ff0000; -} - -div.tpR hr { - border-style: solid; - border-color: #02c; - background-color: #ddf; - border-color: #88f; - border-width: 1px; - padding-top: 1px; - padding-bottom: 1px; -} - -div.pp { - color: #FF0000; -} - -div.infobulle{ - position: absolute; - visibility : hidden; - border: 1px solid Black; - padding: 10px; - font-family: Verdana, Arial; - font-size: 13px; - background-color: #ffffff; - -moz-border-radius: 20px; /* pour avoir des coins arrondis */ -} - -/* http://www.w3schools.com/CSS/css_display_visibility.asp */ -span.commentPub{ - background-color: #77ff33; -} - -span.moreCommentOnPub{ -/* position: absolute;*/ -/* visibility : hidden;*/ -/* border: 1px solid Black; - padding: 10px; - font-family: Verdana, Arial; - font-size: 13px;*/ - background-color: #77ff33; - -moz-border-radius: 3em 1em /* 20px; pour avoir des coins arrondis */ - border-radius: 3em 1em; /* 20px; pour avoir des coins arrondis */ -} diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/Affymetrix.Rmd --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/Affymetrix.Rmd Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,373 @@ + + + Preprocessing Plots Before and After + + + +
+

Preprocessing

+

+Preprocessing of an `r datasetsource` DataSet, issued from +`r technology` +technology. +

+

Used methods for each step

+ +

Background correction methods

+
method : `r listArguments[["backgroundcorrection_method"]]`
+

Normalization methods

+
method : `r listArguments[["normalization_method"]]`
+

Summarization methods

+
method : `r listArguments[["summary_method"]]`
+

Boxplots

+

Before NM

+

+
+ +
+

+

After NM

+

+
+ +
+

+

MA plots

+

+
+ +
+

+

Densities plot

+

Before NM

+

+
+ +
+

+

After NM

+

+
+ +
+

+ + diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/Affymetrix_Preprocessing.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/Affymetrix_Preprocessing.R Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,93 @@ +options(show.error.messages=F, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) +sink(stdout(), type = "message") +suppressWarnings(suppressMessages(library(affy))) +suppressWarnings(suppressMessages(library(affyPLM))) +suppressWarnings(suppressMessages(library(batch))) +suppressWarnings(suppressMessages(library(annotate))) +suppressWarnings(suppressMessages(library(limma))) +suppressWarnings(suppressMessages(library(markdown))) +suppressWarnings(suppressMessages(library(knitr))) +suppressWarnings(suppressMessages(library(BiocInstaller))) +source_local <- function(fname){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + source(paste(base_dir, fname, sep="/")) +} +file_path <- function(fname){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + pato <- paste(base_dir, fname, sep="/") + return(pato) +} +base_dir <- function(){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + return(base_dir) +} +source_local("Affymetrix_Preprocessing_Functions.R") +listArguments = parseCommandArgs(evaluate=FALSE) +thefunctions=listArguments[["thefunctions"]] +listArguments[["thefunctions"]]=NULL +h=listArguments[["h"]] +listArguments[["h"]]=NULL +w=listArguments[["w"]] +listArguments[["w"]]=NULL +if (!is.null(listArguments[["image"]])){ + load(listArguments[["image"]]) + listArguments[["image"]]=NULL +} +listArguments[["path"]]="" +print(listArguments) +listArguments[["rawdata"]]=MicroArray_Object$affy_object +if(datasetsource=="intern"){ +designo<-MicroArray_Object$designo +} + +if(datasetsource=="extern"){ +listArguments<-append(listArguments,list(datasetsource=datasetsource,listfullnames=listfullnames)) +} +Prepro_object<-do.call(thefunctions,listArguments) +if(datasetsource=="extern"){ +rownames(Prepro_object$data.bg@phenoData@data)<-listfullnames +colnames(exprs(Prepro_object$data.bg))<-listfullnames +colnames(exprs(Prepro_object$data.sm))<-listfullnames +colnames(exprs(Prepro_object$data.norm))<-listfullnames +colnames(exprs(Prepro_object$data.bg))<-listfullnames +colnames(exprs(Prepro_object$data.norm))<-listfullnames +rownames(Prepro_object$data.norm@phenoData@data)<-listfullnames +rownames(Prepro_object$data.norm@protocolData@data)<-listfullnames +} +par(las=2,mar=c(15,2,1,1)) +png(filename ="boxplot_before_NM.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") +par(las=2,mar=c(15,2,1,1)) +boxplot((na.omit(as.data.frame(exprs(Prepro_object$data.bg)))), main="Boxplot of intensities before Normalization",col="red",las=2,mar=c(15,2,1,1)) + +dev.off() + + + +par(las=2,mar=c(15,2,1,1)) +png(filename ="boxplot_after_NM.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") +par(las=2,mar=c(15,2,1,1)) +boxplot((na.omit(as.data.frame(exprs(Prepro_object$data.sm)))), main="Boxplot of intensities After Normalization",col="red",ylab="(intensities)",las=2,mar=c(15,2,1,1)) + +dev.off() +png(filename ="MA_plot.png",width = w, height = h) +MAplot((Prepro_object$data.norm) , + show.statistics = F, span = 2/3, family.loess = "gaussian", + cex = 2, plot.method = as.character("smoothScatter"), + azdd.loess = TRUE, lwd = 1, lty = 1, loess.col = "red") + +dev.off() +png(filename = "densities_plot_before_NM.png",width = w, height = h) +plotDensities(exprs(Prepro_object$data.bg),log=T) +dev.off() + +png(filename = "densities_plot_after_NM.png",width = w, height = h) +plotDensities(exprs(Prepro_object$data.norm),log=T) +dev.off() +AffymetrixRmd=file_path("Affymetrix.Rmd") +Style=file_path("look.css") +suppressWarnings(suppressMessages(knit2html(AffymetrixRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) +rm(listArguments) +save.image("MicroArray.Preprocessing.RData") diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/Affymetrix_Preprocessing_Functions.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/Affymetrix_Preprocessing_Functions.R Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,32 @@ +AffymetrixPreprocessingFunction<-function(path="",rawdata,backgroundcorrection_method,normalization_method,summary_method,datasetsource="",listfullnames="") +{ + colnames(exprs(rawdata))<-listfullnames + data.bg<-bg.correct(rawdata, method=backgroundcorrection_method) + data.norm<-normalize(data.bg, method=normalization_method) + data.sm<-threestep(data.norm, background=F, normalize=F,summary.method=summary_method) + data_matrix=exprs(data.sm) + sampleNames(data.sm)<-listfullnames + if(datasetsource=="extern"){ + colnames(data_matrix)<-listfullnames + data.sm=ExpressionSet(data_matrix,phenoData=phenoData(data.sm),featureData=featureData(data.sm), + experimentData=experimentData(data.sm),annotation=annotation(data.sm),protocolData=protocolData(data.sm)) + write.table(format(exprs(data.sm), justify="right"),sep="\t", quote=FALSE, + row.names=T, col.names=T,file="Matrix.Data.tsv") + }else{ + colnames(data_matrix)<-designo$sample + data.sm=ExpressionSet(data_matrix,phenoData=phenoData(data.sm),featureData=featureData(data.sm), + experimentData=experimentData(data.sm),annotation=annotation(data.sm),protocolData=protocolData(data.sm)) + write.table(format(exprs(data.sm), justify="right"),sep="\t", quote=FALSE, + row.names=T, col.names=T,file="Matrix.Data.tsv") + } + installed<-as.data.frame(installed.packages()) + lbraries=paste(annotation(data.sm),"db",sep='.') + if(!lbraries%in%installed$Package){ + biocLite(lbraries[!lbraries%in%installed$Package])} + + suppressWarnings(suppressMessages(library(lbraries,character.only = TRUE))) + + symbol<-getSYMBOL(rownames(exprs(data.sm)), annotation(data.sm)) + return(list(data.bg=data.bg,data.norm=data.norm,data.sm=data.sm,matrix_data=exprs(data.sm),symbol=symbol)) + + } diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/Agilent_One_Color_Preprocessing.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/Agilent_One_Color_Preprocessing.R Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,89 @@ +options(show.error.messages=F, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) +sink(stdout(), type = "message") +suppressWarnings(suppressMessages(library(limma))) +suppressWarnings(suppressMessages(library(batch))) +suppressWarnings(suppressMessages(library(marray))) +suppressWarnings(suppressMessages(library(IDPmisc))) +suppressWarnings(suppressMessages(library(markdown))) +suppressWarnings(suppressMessages(library(knitr))) +source_local <- function(fname){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + source(paste(base_dir, fname, sep="/")) +} +file_path <- function(fname){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + pato <- paste(base_dir, fname, sep="/") + return(pato) +} +base_dir <- function(){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + return(base_dir) +} +source_local("Agilent_One_Color_Preprocessing_Functions.R") +listArguments = parseCommandArgs(evaluate=FALSE) +print(listArguments) +load(listArguments[["image"]]) +names(listArguments)[which(names(listArguments)=="image")]="data" +listArguments[["data"]]=MicroArray_Object$RFile +if(datasetsource=="intern"){ +designo<-MicroArray_Object$designo +} +thefunction=listArguments[["thefunction"]] +listArguments[["thefunction"]]=NULL +listArguments[["thefunctions"]]=NULL +h=listArguments[["h"]] +listArguments[["h"]]=NULL +w=listArguments[["w"]] +listArguments[["w"]]=NULL +Prepro_object<-do.call(thefunction,listArguments) +if(datasetsource=="extern"){ +colnames(MicroArray_Object[[1]]$E)<-listfullnames +colnames(Prepro_object$dataBG$E)<-listfullnames +colnames(Prepro_object$dataNBA$E)<-listfullnames +colnames(MicroArray_Object[[1]]@.Data[[1]])<-listcelsnames[-1] +colnames(MicroArray_Object[[1]]@.Data[[2]])<-listcelsnames[-1] +rownames(MicroArray_Object[[1]]@.Data[[3]])<-listcelsnames[-1] +MicroArray_Object[[1]]@.Data[[3]]$FileName<-listfullnames +colnames(Prepro_object$dataBG@.Data[[1]])<-listcelsnames[-1] +Prepro_object$dataBG@.Data[[2]]$FileName<-listfullnames +colnames(Prepro_object$dataNBA[[1]])<-listcelsnames[-1] +Prepro_object$dataNBA[[2]]$FileName<-listfullnames +} +par(las=2,mar=c(15,2,1,1)) +png(filename ="boxplot_before_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") +boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$E))), main="Boxplot of log2( intensities) before Background Correction",col="red",ylab="log2( intensities)",xlab="",las=2,mar=c(15,2,1,1)) + +dev.off() + +png(filename ="boxplot_after_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") + +boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$E))), main="Boxplot of log2( intensities) After Background Correction",col="red",ylab="log2( intensities)",xlab="",las=2,mar=c(15,2,1,1)) + +dev.off() + + +png(filename ="boxplot_after_NBA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") + +boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNBA$E))), main="Boxplot of log2( intensities) After Normalization Between Arrays",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) + +dev.off() +png(filename = "densities_plot_before_BG.png",width = w, height = h) +plotDensities(MicroArray_Object[[1]],log=T) +dev.off() + +png(filename = "densities_plot_after_BG.png",width = w, height = h) +plotDensities(Prepro_object$dataBG,log=T) +dev.off() + + +png(filename = "densities_plot_after_NBA.png",width = w, height = h) +plotDensities(Prepro_object$dataNBA,log=T) +dev.off() +OneColorRmd=file_path("OneColor.Rmd") +Style=file_path("look.css") +suppressWarnings(suppressMessages(knit2html(OneColorRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) +rm(listArguments) +save.image("MicroArray.Preprocessing.RData") diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/Agilent_One_Color_Preprocessing_Functions.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/Agilent_One_Color_Preprocessing_Functions.R Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,17 @@ +AgilentOneColorPreprocessingFunction<- function(path,data,methodBC,methodNBA) +{ +MA <<- backgroundCorrect(data, method=methodBC ,offset = 2) +rownames(MA$E)=MA$genes$ProbeName +MA<-MA[rm.na(rownames(MA$E)),] +MAb <<-suppressWarnings(suppressMessages(normalizeBetweenArrays(MA, method=methodNBA))) +data_mt<-NaRV.omit(as.data.frame(MAb$E)) +MAb$E=(data_mt) +MAb$genes=(MAb$genes[(MAb$genes$ProbeName %in% rownames(MAb$E)),]) +MA.avg <-suppressWarnings(suppressMessages(avereps(MAb, ID=MAb$genes$ProbeName))) +data_matrix=NaRV.omit(MA.avg$E) +colnames(data_matrix)<-designo$sample +write.table(format(data_matrix, justify="right"),sep="\t", quote=FALSE, + row.names=T, col.names=T,file="Matrix.Data.tsv") + +return(list(dataNBA=MA.avg,dataBG=MA,matrix_data=as.matrix(MA.avg$E),symbol=MA.avg$genes$GeneName)) +} diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/Agilent_Two_Colors_Preprocessing.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/Agilent_Two_Colors_Preprocessing.R Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,113 @@ +options(show.error.messages=F, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) +sink(stdout(), type = "message") +suppressWarnings(suppressMessages(library(limma))) +suppressWarnings(suppressMessages(library(batch))) +suppressWarnings(suppressMessages(library(marray))) +suppressWarnings(suppressMessages(library(IDPmisc))) +suppressWarnings(suppressMessages(library(affy))) +suppressWarnings(suppressMessages(library(markdown))) +suppressWarnings(suppressMessages(library(knitr))) +source_local <- function(fname){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + source(paste(base_dir, fname, sep="/")) +} +file_path <- function(fname){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + pato <- paste(base_dir, fname, sep="/") + return(pato) +} +base_dir <- function(){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + return(base_dir) +} +source_local("Make_matrix_two_channels.R") +source_local("Agilent_Two_Colors_Preprocessing_Functions.R") +listArguments = parseCommandArgs(evaluate=FALSE) +print(listArguments) +# print(thefunction) +load(listArguments[["image"]]) +names(listArguments)[which(names(listArguments)=="image")]="data" +listArguments[["data"]]=MicroArray_Object$RFile + +thefunction=listArguments[["thefunction"]] +listArguments[["thefunction"]]=NULL +h=listArguments[["h"]] +listArguments[["h"]]=NULL +w=listArguments[["w"]] +listArguments[["w"]]=NULL +# print(thefunction) +if(datasetsource=="intern"){ +designo<-MicroArray_Object$designo +} + +Prepro_object<-do.call(thefunction,listArguments) +designo<-Prepro_object$designo +RGNBA=RG.MA(Prepro_object$dataNBA) +if(datasetsource=="extern"){ +colnames(MicroArray_Object[[1]]$G)<-listcelsnames[-1] +colnames(MicroArray_Object[[1]]$R)<-listcelsnames[-1] +colnames(Prepro_object$dataBG$G)<-listcelsnames[-1] +colnames(Prepro_object$dataBG$R)<-listcelsnames[-1] +colnames(Prepro_object$dataNWA$G)<-listcelsnames[-1] +colnames(Prepro_object$dataNWA$R)<-listcelsnames[-1] +colnames(RGNBA$G)<-listcelsnames[-1] +colnames(RGNBA$R)<-listcelsnames[-1] + +} +par(las=2,mar=c(15,2,1,1)) +png(filename ="boxplot_before_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") +old.par <- par(mfrow=c(1, 2)) +boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$R))), main="Boxplot of log2(R intensities) before BGC",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) +boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$G))), main="Boxplot of log2(G intensities) before BGC",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) +par(old.par) +dev.off() + +png(filename ="boxplot_after_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") +old.par <- par(mfrow=c(1, 2)) +boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$R))), main="Boxplot of log2(R intensities) After BGC",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) +boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$G))), main="Boxplot of log2(G intensities) After BGC",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) +par(old.par) +dev.off() + +png(filename ="boxplot_after_NWA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") +old.par <- par(mfrow=c(1, 2)) +boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNWA$R))), main="Boxplot of log2(R intensities) After NWA",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) +boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNWA$G))), main="Boxplot of log2(G intensities) After NWA",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) +par(old.par) +dev.off() +png(filename ="boxplot_after_NBA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") +old.par <- par(mfrow=c(1, 2)) +boxplot(log2(na.omit(as.data.frame(RGNBA$R))), main="Boxplot of log2(R intensities) After NBA",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) +boxplot(log2(na.omit(as.data.frame(RGNBA$G))), main="Boxplot of log2(G intensities) After NBA",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) +par(old.par) +dev.off() +png(filename ="MA_plot.png",width = w, height = h) +ma.plot(na.omit(Prepro_object$dataNBA$A), na.omit(Prepro_object$dataNBA$M), + show.statistics = F, span = 2/3, family.loess = "gaussian", + cex = 2, plot.method = as.character("smoothScatter"), + add.loess = TRUE, lwd = 1, lty = 1, loess.col = "red",main="MA plot") + +dev.off() +png(filename = "densities_plot_before_BG.png",width = w, height = h) +plotDensities(MicroArray_Object[[1]],log=T) +dev.off() + +png(filename = "densities_plot_after_BG.png",width = w, height = h) +plotDensities(Prepro_object$dataBG,log=T) +dev.off() + +png(filename = "densities_plot_after_NWA.png",width = w, height = h) +plotDensities(Prepro_object$dataNWA,log=T) +dev.off() + +png(filename = "densities_plot_after_NBA.png",width = w, height = h) +plotDensities(Prepro_object$dataNBA,log=T) +dev.off() +TwoColorsRmd=file_path("TwoColors.Rmd") +Style=file_path("look.css") +suppressWarnings(suppressMessages(knit2html(TwoColorsRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) +rm(listArguments) +save.image("MicroArray.Preprocessing.RData") diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/Agilent_Two_Colors_Preprocessing_Functions.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/Agilent_Two_Colors_Preprocessing_Functions.R Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,21 @@ +AgilentTwoChannelsPreprocessingFunction<- function(path,data,methodBC,methodNWA,methodNBA) +{ + RG <<- suppressWarnings(suppressMessages(backgroundCorrect(data,method=methodBC, offset= 16))) + MA <<- suppressWarnings(suppressMessages(normalizeWithinArrays(RG, method=methodNWA,bc.method="none"))) + rownames(MA$A)=rownames(MA$M)=MA$gene$ProbeName + MA<-MA[rm.na(rownames(MA$M)),] + MAb <<- suppressWarnings(suppressMessages(normalizeBetweenArrays(MA, method=methodNBA))) + data_mt<-NaRV.omit(as.data.frame(MAb$M)) + MAb$M=(data_mt) + MAb$A=NaRV.omit(as.data.frame(MAb$A)) + MAb$genes=(MAb$genes[(MAb$genes$ProbeName %in% c(rownames(MAb$A),rownames(MAb$M))),]) + RG.pq <<- RG.MA(MA) + MA.avg <- suppressWarnings(suppressMessages(avereps(MAb,ID=MAb$genes$ProbeName))) + data_matrix=NaRV.omit(MA.avg$M) + colnames(data_matrix)<-designo$sample + write.table(format(data_matrix, justify="right"),sep="\t", quote=FALSE, + row.names=T, col.names=T,file="Matrix.Data.tsv") + Prepro_object1<-list(dataBG=RG,dataNWA=RG.pq,dataNBA=MA.avg,matrix_data=as.matrix(data_matrix),symbol=(MA.avg$genes$GeneName)) + Prepro_object1=make_design(MA_matrix=Prepro_object1) + return(Prepro_object1) +} diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/GenePix_One_Color_Preprocessing.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/GenePix_One_Color_Preprocessing.R Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,91 @@ +options(show.error.messages=F, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) +sink(stdout(), type = "message") +suppressWarnings(suppressMessages(library(limma))) +suppressWarnings(suppressMessages(library(marray))) +suppressWarnings(suppressMessages(library(batch))) +suppressWarnings(suppressMessages(library(IDPmisc))) +suppressWarnings(suppressMessages(library(markdown))) +suppressWarnings(suppressMessages(library(knitr))) +source_local <- function(fname){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + source(paste(base_dir, fname, sep="/")) +} +file_path <- function(fname){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + pato <- paste(base_dir, fname, sep="/") + return(pato) +} +base_dir <- function(){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + return(base_dir) +} +source_local("GenePix_One_Color_Preprocessing_Functions.R") +listArguments = parseCommandArgs(evaluate=FALSE) +print(listArguments) +load(listArguments[["image"]]) +names(listArguments)[which(names(listArguments)=="image")]="data" +listArguments[["data"]]=MicroArray_Object$RFile +if(datasetsource=="intern"){ +designo<-MicroArray_Object$designo +} +thefunction=listArguments[["thefunction"]] +listArguments[["thefunction"]]=NULL +listArguments[["thefunctions"]]=NULL +h=listArguments[["h"]] +listArguments[["h"]]=NULL +w=listArguments[["w"]] +listArguments[["w"]]=NULL +Prepro_object<-do.call(thefunction,listArguments) +RGNBA=RG.MA(Prepro_object$dataNBA) +if(datasetsource=="extern"){ +colnames(MicroArray_Object[[1]]$E)<-listfullnames# +colnames(Prepro_object$dataBG$E)<-listfullnames# +colnames(Prepro_object$dataNBA$E)<-listfullnames# +colnames(MicroArray_Object[[1]]@.Data[[1]])<-listcelsnames[-1]# +colnames(MicroArray_Object[[1]]@.Data[[2]])<-listcelsnames[-1]# +rownames(MicroArray_Object[[1]]@.Data[[3]])<-listcelsnames[-1]# +MicroArray_Object[[1]]@.Data[[3]]$FileName<-listfullnames# +colnames(Prepro_object$dataBG@.Data[[1]])<-listcelsnames[-1]# +Prepro_object$dataBG@.Data[[2]]$FileName<-listfullnames# +colnames(Prepro_object$dataNBA[[1]])<-listcelsnames[-1]# +Prepro_object$dataNBA[[2]]$FileName<-listfullnames# +} +par(las=2,mar=c(15,2,1,1)) +png(filename ="boxplot_before_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") + +boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$E))), main="Boxplot of log2( intensities) before Background Correction",col="red",ylab="log2( intensities)",xlab="",las=2,mar=c(15,2,1,1)) + +dev.off() + +png(filename ="boxplot_after_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") + +boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$E))), main="Boxplot of log2( intensities) After Background Correction",col="red",ylab="log2( intensities)",xlab="",las=2,mar=c(15,2,1,1)) + +dev.off() + + +png(filename ="boxplot_after_NBA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") + +boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNBA$E))), main="Boxplot of log2( intensities) After Normalization Between Arrays",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) + +dev.off() +png(filename = "densities_plot_before_BG.png",width = w, height = h) +plotDensities(MicroArray_Object[[1]],log=T) +dev.off() + +png(filename = "densities_plot_after_BG.png",width = w, height = h) +plotDensities(Prepro_object$dataBG,log=T) +dev.off() + + +png(filename = "densities_plot_after_NBA.png",width = w, height = h) +plotDensities(Prepro_object$dataNBA,log=T) +dev.off() +OneColorRmd=file_path("OneColor.Rmd") +Style=file_path("look.css") +suppressWarnings(suppressMessages(knit2html(OneColorRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) +rm(listArguments) +save.image("MicroArray.Preprocessing.RData") diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/GenePix_One_Color_Preprocessing_Functions.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/GenePix_One_Color_Preprocessing_Functions.R Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,17 @@ +GenePixOneColorPreprocessingFunction<- function(path,data,methodBC,methodNBA) +{ + MA <<- suppressWarnings(suppressMessages(backgroundCorrect(data, method=methodBC ,offset = 16))) + rownames(MA$E)=MA$genes$ID + MA<-MA[rm.na(rownames(MA$E)),] + MAb <<-suppressWarnings(suppressMessages(normalizeBetweenArrays(MA, method=methodNBA))) + data_mt<-NaRV.omit(as.data.frame(MAb$E)) + MAb$E=(data_mt) + MAb$genes=(MAb$genes[(MAb$genes$ID %in% rownames(MAb$E)),]) + MA.avg <-suppressWarnings(suppressMessages(avereps(MAb, ID=MAb$genes$ID))) + data_matrix=NaRV.omit(MA.avg$E) + colnames(data_matrix)<-designo$sample + write.table(format(data_matrix, justify="right"),sep="\t", quote=FALSE, + row.names=T, col.names=T,file="Matrix.Data.tsv") + return(list(dataNBA=MA.avg,dataBG=MA,matrix_data=as.matrix(MA.avg$E),symbol=MA.avg$genes$Name)) +} + diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/GenePix_Two_Colors_Preprocessing.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/GenePix_Two_Colors_Preprocessing.R Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,110 @@ +options(show.error.messages=F, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) +sink(stdout(), type = "message") +suppressWarnings(suppressMessages(library(limma))) +suppressWarnings(suppressMessages(library(marray))) +suppressWarnings(suppressMessages(library(batch))) +suppressWarnings(suppressMessages(library(IDPmisc))) +suppressWarnings(suppressMessages(library(affy))) +suppressWarnings(suppressMessages(library(markdown))) +suppressWarnings(suppressMessages(library(knitr))) +source_local <- function(fname){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + source(paste(base_dir, fname, sep="/")) +} +file_path <- function(fname){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + pato <- paste(base_dir, fname, sep="/") + return(pato) +} +base_dir <- function(){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + return(base_dir) +} +source_local("Make_matrix_two_channels.R") +source_local("GenePix_Two_Colors_Preprocessing_Functions.R") +listArguments = parseCommandArgs(evaluate=FALSE) +print(listArguments) +load(listArguments[["image"]]) +names(listArguments)[which(names(listArguments)=="image")]="data" +listArguments[["data"]]=MicroArray_Object$RFile +thefunction=listArguments[["thefunction"]] +listArguments[["thefunction"]]=NULL +h=listArguments[["h"]] +listArguments[["h"]]=NULL +w=listArguments[["w"]] +listArguments[["w"]]=NULL +# print(thefunction) +if(datasetsource=="intern"){ +designo<-MicroArray_Object$designo +} +Prepro_object<-do.call(thefunction,listArguments) +designo<-Prepro_object$designo +RGNBA=RG.MA(Prepro_object$dataNBA) +if(datasetsource=="extern"){ +colnames(MicroArray_Object[[1]]$G)<-listcelsnames[-1] +colnames(MicroArray_Object[[1]]$R)<-listcelsnames[-1] +colnames(Prepro_object$dataBG$G)<-listcelsnames[-1] +colnames(Prepro_object$dataBG$R)<-listcelsnames[-1] +colnames(Prepro_object$dataNWA$G)<-listcelsnames[-1] +colnames(Prepro_object$dataNWA$R)<-listcelsnames[-1] +colnames(RGNBA$G)<-listcelsnames[-1] +colnames(RGNBA$R)<-listcelsnames[-1] + +} +par(las=2,mar=c(15,2,1,1)) +png(filename ="boxplot_before_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") +old.par <- par(mfrow=c(1, 2)) +boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$R))), main="Boxplot of log2(R intensities) before BGC",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) +boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$G))), main="Boxplot of log2(G intensities) before BGC",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) +par(old.par) +dev.off() + +png(filename ="boxplot_after_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") +old.par <- par(mfrow=c(1, 2)) +boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$R))), main="Boxplot of log2(R intensities) After BGC",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) +boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$G))), main="Boxplot of log2(G intensities) After BGC",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) +par(old.par) +dev.off() + +png(filename ="boxplot_after_NWA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") +old.par <- par(mfrow=c(1, 2)) +boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNWA$R))), main="Boxplot of log2(R intensities) After NWA",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) +boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNWA$G))), main="Boxplot of log2(G intensities) After NWA",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) +par(old.par) +dev.off() +png(filename ="boxplot_after_NBA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") +old.par <- par(mfrow=c(1, 2)) +boxplot(log2(na.omit(as.data.frame(RGNBA$R))), main="Boxplot of log2(R intensities) After NBA",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) +boxplot(log2(na.omit(as.data.frame(RGNBA$G))), main="Boxplot of log2(G intensities) After NBA",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) +par(old.par) +dev.off() +png(filename ="MA_plot.png",width = w, height = h) +ma.plot(na.omit(Prepro_object$dataNBA$A), na.omit(Prepro_object$dataNBA$M), + show.statistics = F, span = 2/3, family.loess = "gaussian", + cex = 2, plot.method = as.character("smoothScatter"), + add.loess = TRUE, lwd = 1, lty = 1, loess.col = "red",main="MA plot") + +dev.off() +png(filename = "densities_plot_before_BG.png",width = w, height = h) +plotDensities(MicroArray_Object[[1]],log=T) +dev.off() + +png(filename = "densities_plot_after_BG.png",width = w, height = h) +plotDensities(Prepro_object$dataBG,log=T) +dev.off() + +png(filename = "densities_plot_after_NWA.png",width = w, height = h) +plotDensities(Prepro_object$dataNWA,log=T) +dev.off() + +png(filename = "densities_plot_after_NBA.png",width = w, height = h) +plotDensities(Prepro_object$dataNBA,log=T) +dev.off() +TwoColorsRmd=file_path("TwoColors.Rmd") +Style=file_path("look.css") +suppressWarnings(suppressMessages(knit2html(TwoColorsRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) +rm(listArguments) +save.image(file="MicroArray.Preprocessing.RData") diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/GenePix_Two_Colors_Preprocessing_Functions.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/GenePix_Two_Colors_Preprocessing_Functions.R Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,21 @@ +GenePixTwoChannelsPreprocessingFunction<- function(path,data,methodBC,methodNWA,methodNBA) +{ + RG <<- backgroundCorrect(data,method=methodBC, offset=64) + MA <<- suppressWarnings(suppressMessages(normalizeWithinArrays(RG, method=methodNWA,bc.method="none"))) + rownames(MA$A)=rownames(MA$M)=MA$gene$ID + MA<-MA[rm.na(rownames(MA$M)),] + RG.pq <<- RG.MA(MA) + MAb <<-suppressWarnings(suppressMessages(normalizeBetweenArrays(MA, method=methodNBA))) + data_mt<-NaRV.omit(as.data.frame(MAb$M)) + MAb$M=(data_mt) + MAb$A=NaRV.omit(as.data.frame(MAb$A)) + MAb$genes=(MAb$genes[(MAb$genes$ID %in% c(rownames(MAb$A),rownames(MAb$M))),]) + MA.avg <-suppressWarnings(suppressMessages(avereps(MAb, ID=MAb$genes$ID))) + data_matrix=NaRV.omit(MA.avg$M) + colnames(data_matrix)<-designo$sample + write.table(format(data_matrix, justify="right"),sep="\t", quote=FALSE, + row.names=T, col.names=T,file="Matrix.Data.tsv") + +return(make_design(MA_matrix=list(dataBG=RG,dataNWA=RG.pq,dataNBA=MA.avg,matrix_data=as.matrix(data_matrix),symbol=MA.avg$genes$Name))) +} + diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/Make_matrix_two_channels.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/Make_matrix_two_channels.R Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,28 @@ +make_design<-function(MA_matrix){ + matrix<-RG.MA(MA_matrix$dataNBA) + colnames_matrix<-NULL + tmp<-strsplit(colnames(MA_matrix$dataNBA),split=".",fixed = T) + for(i in 1:ncol(MA_matrix$dataNBA)){ + colnames_matrix[i]<-paste(tmp[[i]][1],"R",sep=".") + + # .Red intensity + } + i=1; + for(j in (ncol(MA_matrix$dataNBA)+1):((ncol(MA_matrix$dataNBA)*2))){ + + colnames_matrix[j]<-paste(tmp[[i]][1],"G",sep=".") + i<-i+1; + # .Green intensity + } + matrix_data<-cbind(matrix$R,matrix$G) + colnames(matrix_data)<-colnames_matrix + rownames(matrix_data)<-rownames(MA_matrix$dataNBA) + MA_matrix$matrix_data<-log2(matrix_data) + groupe<-c(rep("case",ncol(matrix$R)),rep("control",ncol(matrix$G))) + sample=colnames(matrix_data) + designo<-data.frame(sample=sample,groupetype=rep(designo$group,2),group=groupe) + MA_matrix$designo<-designo + write.table(format(designo, justify="right"),sep="\t", quote=FALSE, + row.names=T, col.names=T,file="design.txt") + return(MA_matrix) +} diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/OneColor.Rmd --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/OneColor.Rmd Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,370 @@ + + + Preprocessing Plots Before and After + + + +
+

Preprocessing

+

+Preprocessing of an `r datasetsource` DataSet, issued from +`r technology` +technology. +

+

Used methods for each step

+ +

Background correction methods

+
method : `r listArguments[["methodBC"]]`
+

Normalization methods

+
method : `r listArguments[["methodNBA"]]`
+

Boxplots

+

Before BG

+

+
+ +
+

+

After NBA

+

+
+ +
+

+

Densities plot

+

Before BG

+

+
+ +
+

+

After BG and NBA

+

+
+ +
+

+

+
+ +
+

+ + diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/Preprocess_DataSet.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/Preprocess_DataSet.xml Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,306 @@ + + Preprocessing microarrays datasets.Contains Background Correction, Normalization within arrays, between arrays (depending on the number of channels) and summarization. + + citations.xml + + + r-base + r-batch + bioconductor-affyplm + bioconductor-affy + bioconductor-annotate + r-knitr + bioconductor-marray + r-idpmisc + r-kernsmooth + r-rmarkdown + r-markdown + bioconductor-limma + r-idpmisc + + + + + + + + + + 'Read.Project' in value.name + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +.. class:: infomark + +**Authors** T.Bensellak, B.Ettetuani. + +--------------------------------------------------- + +================================== +Preprocessing Microarray DataSet +================================== + +----------- +Description +----------- + +This tool is used as first phase of the global workflow, the preprocessing . + +----------------- +Workflow position +----------------- + +**Upstream tools** + ++-------------------------------+------------------------------+---------+ +| Name | output file |format | ++===============================+==============================+=========+ +| Read.DataSet.Microarray | MicroArrayObject.RData | Rdat | ++-------------------------------+------------------------------+---------+ + + +**Downstream tools** + ++-----------------------------------------------+----------------------------------------------+---------+ +| Name | Output file | Format | ++===============================================+==============================================+=========+ +|Tests and Selection | Test.results.tsv | Tabular | ++-----------------------------------------------+----------------------------------------------+---------+ + +----------- +Input files +----------- + ++---------------------------+------------+ +| Parameter : num + label | Format | ++===========================+============+ +| Image | Rdata | ++---------------------------+------------+ +| Methods parmeters | Numeric | ++---------------------------+------------+ + +------------ +Output files +------------ + +**Microarray.Preprocessing.RData** + +**Matrix.Data.tsv** + +------------------------------ +General schema of the workflow +------------------------------ + +https://bensellak.github.io/microarrays-galaxy/workflow.png + + + + + + diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/TwoColors.Rmd --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/TwoColors.Rmd Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,387 @@ + + + Preprocessing Plots Before and After + + + +
+

Preprocessing

+

+Preprocessing of an `r datasetsource` DataSet, issued from +`r technology` +technology. +

+

Used methods for each step

+ +

Background correction methods

+
method : `r listArguments[["methodBC"]]`
+

Normalization methods

+
methodNWA : `r listArguments[["methodNWA"]]`
+
methodNBA : `r listArguments[["methodNBA"]]`
+

Boxplots

+

Before BG

+

+
+ +
+

+

After BG, NWA and NBA

+

+
+ +
+

+

+
+ +
+

+

+
+ +
+

+

MA plots

+

+
+ +
+

+

Densities plot

+

Before BG

+

+
+ +
+

+

After BG and NWA

+

+
+ +
+

+

+
+ +
+

+ + diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/citations.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/citations.xml Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,113 @@ + + 1.0 + + + + @Manual{, + title = {R: A Language and Environment for Statistical Computing}, + author = {{R Core Team}}, + organization = {R Foundation for Statistical Computing}, + address = {Vienna, Austria}, + year = {2017}, + url = {https://www.R-project.org/}, + } + + + @Article{, + title = {Passing in Command Line Arguments and Parallel Cluster/Multicore Batching in {R} with {batch}}, + author = {Thomas J. Hoffmann}, + journal = {Journal of Statistical Software, Code Snippets}, + year = {2011}, + volume = {39}, + number = {1}, + pages = {1--11}, + url = {http://www.jstatsoft.org/v39/c01/}, + } + + + @Article{, + author = {Laurent Gautier and Leslie Cope and Benjamin M. Bolstad and Rafael A. Irizarry}, + title = {affy---analysis of Affymetrix GeneChip data at the probe level}, + journal = {Bioinformatics}, + volume = {20}, + number = {3}, + year = {2004}, + issn = {1367-4803}, + pages = {307--315}, + doi = {10.1093/bioinformatics/btg405}, + publisher = {Oxford University Press}, + address = {Oxford, UK}, + } + + + @Article{, + author = {Matthew E Ritchie and Belinda Phipson and Di Wu and Yifang Hu and Charity W Law and Wei Shi and Gordon K Smyth}, + title = {{limma} powers differential expression analyses for {RNA}-sequencing and microarray studies}, + journal = {Nucleic Acids Research}, + year = {2015}, + volume = {43}, + number = {7}, + pages = {e47}, + } + + + @Article{, + title = {Quality assessment for short oligonucleotide arrays.}, + author = {Julia Brettschneider and Francois Collin and Benjamin M Bolstad and Terence P Speed}, + journal = {Technometrics}, + year = {2007}, + volume = {In press}, + } + + + @Manual{, + title = {annotate: Annotation for microarrays}, + author = {R. Gentleman}, + year = {2017}, + note = {R package version 1.56.0}, + } + + + @Manual{, + title = {knitr: A General-Purpose Package for Dynamic Report Generation in R}, + author = {Yihui Xie}, + year = {2017}, + note = {R package version 1.16}, + url = {http://yihui.name/knitr/}, + } + + + @Manual{, + title = {marray: Exploratory analysis for two-color spotted microarray data}, + author = {Yee Hwa Yang with contributions from Agnes Paquet and Sandrine Dudoit.}, + year = {2009}, + note = {R package version 1.58.0}, + url = {http://www.maths.usyd.edu.au/u/jeany/}, + } + + + @Manual{, + title = {IDPmisc: Utilities of Institute of Data Analyses and Process Design +(www.idp.zhaw.ch)}, + author = {Rene Locher and Andreas Ruckstuhl et al.}, + year = {2012}, + note = {R package version 1.1.17}, + url = {https://CRAN.R-project.org/package=IDPmisc}, + } + + + @Manual{, + title = {KernSmooth: Functions for Kernel Smoothing Supporting Wand and Jones (1995)}, + author = {Matt Wand}, + year = {2015}, + note = {R package version 2.23-15}, + url = {https://CRAN.R-project.org/package=KernSmooth}, + } + + + + + + + + diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/preprocess_datasets/look.css --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/preprocess_datasets/look.css Sun Dec 03 14:06:08 2023 +0000 @@ -0,0 +1,317 @@ +/* css racine */ + +body { +/* font-family: Comic Sans MS;*/ +} + +div.research { + background-color: #33ffff; /*#208090 */ /*#228491*/; + color: #0000ff; /* ffffff */ +} + +div.ensg { + background-color: #bbee00; + color: #0000ff; +} + +div.research span.invisible { + visibility:hidden; +} + +kbd { + color: #000000; +} + +pre { + color: #000000; +} + +A:link { + color: #0000ee; /*#ffffff;*/ +} + +A:active { + color: #ff0000; /* #ffffff */ +} + +A:hover { +/* font-size: 2em; */ + text-decoration: none; + color: #0000ee; /* ffffff */ + background-color: #FFFF33; +} + +h3 { + color: #FF0000; +} + +h4 { + color: #FF0000; +} + +div.correction { 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+ + Preprocessing Plots Before and After + + + +

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Preprocessing

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+Preprocessing of an extern DataSet, issued from +GenePix_Two_Colors +technology. +

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Used methods for each step

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Background correction methods

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method : auto
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Normalization methods

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methodNWA : median
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methodNBA : quantile
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Boxplots

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Before BG

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After BG, NWA and NBA

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MA plots

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Densities plot

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Before BG

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After BG

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1.376196350 -0.969329515 -0.239935191 -1.803087805 -1.660314342 -5A10 0.592438126 0.687206504 1.111643069 0.177746697 -0.205772783 -0.096446940 -0.721558025 -0.695915039 -5A12 0.521511011 0.346588933 1.915750244 2.056182912 3.425891956 4.078232707 1.527437141 1.951658153 diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/test-data/Preprocess.Project.Data.RData Binary file preprocess_datasets/test-data/Preprocess.Project.Data.RData has changed diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/test-data/Preprocess_DataSet.xml --- a/preprocess_datasets/test-data/Preprocess_DataSet.xml Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,307 +0,0 @@ - - Preprocessing microarrays datasets.Contains Background Correction, Normalization within arrays, between arrays (depending on the number of channels) and summarization. - - citations.xml - - - r-base - r-batch - bioconductor-affyplm - bioconductor-affy - bioconductor-annotate - r-knitr - bioconductor-marray - r-idpmisc - r-kernsmooth - r-rmarkdown - r-markdown - bioconductor-limma - r-idpmisc - - - - - - - - - - - 'Read.Project' in value.name - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -.. class:: infomark - -**Authors** T.Bensellak, B.Ettetuani. - ---------------------------------------------------- - -================================== -Preprocessing Microarray DataSet -================================== - ------------ -Description ------------ - -This tool is used as first phase of the global workflow, the preprocessing . - ------------------ -Workflow position ------------------ - -**Upstream tools** - -+-------------------------------+------------------------------+---------+ -| Name | output file |format | -+===============================+==============================+=========+ -| Read.DataSet.Microarray | MicroArrayObject.RData | Rdat | -+-------------------------------+------------------------------+---------+ - - -**Downstream tools** - -+-----------------------------------------------+----------------------------------------------+---------+ -| Name | Output file | Format | -+===============================================+==============================================+=========+ -|Tests and Selection | Test.results.tsv | Tabular | -+-----------------------------------------------+----------------------------------------------+---------+ - ------------ -Input files ------------ - -+---------------------------+------------+ -| Parameter : num + label | Format | -+===========================+============+ -| Image | Rdata | -+---------------------------+------------+ -| Methods parmeters | Numeric | -+---------------------------+------------+ - ------------- -Output files ------------- - -**Microarray.Preprocessing.RData** - -**Matrix.Data.tsv** - ------------------------------- -General schema of the workflow ------------------------------- - -https://bensellak.github.io/microarrays-galaxy/workflow.png - - - - - - diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/test-data/Preprocessing.Plots.html --- a/preprocess_datasets/test-data/Preprocessing.Plots.html Sun Dec 03 14:02:34 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,762 +0,0 @@ - - - - - -Preprocessing - - - - - - - - - - - - - - -

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MA plots

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- - - - diff -r 9a7f56a398fa -r 09a8947f1031 preprocess_datasets/test-data/Read.Project.Data.RData Binary file preprocess_datasets/test-data/Read.Project.Data.RData has changed