# HG changeset patch # User proteomisc # Date 1702729722 0 # Node ID 4f7fbd73a7704eb9890a2fb5e484b0dd907ffd6d # Parent e80d3d455db7bb72652945acf5b78130d946d752 Deleted selected files diff -r e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/Agilent_One_Color_Preprocessing_Functions.R --- a/preprocess_datasets/Agilent_One_Color_Preprocessing_Functions.R Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,18 +0,0 @@ -AgilentOneColorPreprocessingFunction<- function(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$E)),] -MAb$E=MAb$E[rownames(MAb$E) %in% MAb$genes$ProbeName,] -MA.avg <-suppressWarnings(suppressMessages(avereps(MAb, ID=rownames(MAb$E)))) -data_matrix=NaRV.omit(MA.avg$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 e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/Affymetrix.Rmd --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/Affymetrix.Rmd Sat Dec 16 12:28:07 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"]]`
-

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

-

-
- -
-

- - \ No newline at end of file diff -r e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/Affymetrix_Preprocessing.R --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/Affymetrix_Preprocessing.R Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,91 +0,0 @@ -options(show.error.messages=F,warn=-1, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) -sink(stdout(), type = "message") -sink(stdout() ,type = "output") -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))) -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[["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 -} - -png(filename ="boxplot_before_NM.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -boxplot((na.omit(as.data.frame(exprs(Prepro_object$data.bg)))), main="Boxplot of intensities before Normalization",col="red",las=2,mar=c(15,2,1,1)) -invisible(dev.off()) - -png(filename ="boxplot_after_NM.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -boxplot((na.omit(as.data.frame(exprs(Prepro_object$data.sm)))), main="Boxplot of intensities After Normalization",col="red",ylab="(intensities)",las=2,mar=c(15,2,1,1)) -invisible(dev.off()) - -png(filename ="MA_plot.png",width = w, height = h) -MAplot((Prepro_object$data.norm) , - show.statistics = F, span = 2/3, family.loess = "gaussian", - cex = 2, plot.method = as.character("smoothScatter"), - azdd.loess = TRUE, lwd = 1, lty = 1, loess.col = "red") - -invisible(dev.off()) - -png(filename = "densities_plot_before_NM.png",width = w, height = h) -plotDensities(exprs(Prepro_object$data.bg),log=T) -invisible(dev.off()) - -png(filename = "densities_plot_after_NM.png",width = w, height = h) -plotDensities(exprs(Prepro_object$data.norm),log=T) -invisible(dev.off()) - -AffymetrixRmd=file_path("Affymetrix.Rmd") -Style=file_path("look.css") -suppressWarnings(suppressMessages(knit2html(AffymetrixRmd,output="PreprocessingPlots.html",quiet = T))) -#suppressWarnings(suppressMessages(markdownToHTML(AffymetrixRmd,output="PreprocessingPlots.html", stylesheet=Style))) -#suppressWarnings(suppressMessages(knit2html(AffymetrixRmd,output="PreprocessingPlots.html",quiet = T))) -rm(listArguments) -save.image("MicroArray.Preprocessing.RData") -sink() -sink() diff -r e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/Affymetrix_Preprocessing_Functions.R --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/Affymetrix_Preprocessing_Functions.R Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,33 +0,0 @@ -AffymetrixPreprocessingFunction<-function(rawdata,backgroundcorrection_method,normalization_method,summary_method,datasetsource="",listfullnames="") -{ - colnames(exprs(rawdata))<-listfullnames - data.bg<-bg.correct(rawdata, method=backgroundcorrection_method) - data.norm<-normalize(data.bg, method=normalization_method) - data.sm<-threestep(data.norm, background=F, normalize=F,summary.method=summary_method) - data_matrix=exprs(data.sm) - sampleNames(data.sm)<-listfullnames - if(datasetsource=="extern"){ - colnames(data_matrix)<-listfullnames - data.sm=ExpressionSet(data_matrix,phenoData=phenoData(data.sm),featureData=featureData(data.sm), - experimentData=experimentData(data.sm),annotation=annotation(data.sm),protocolData=protocolData(data.sm)) - write.table(format(exprs(data.sm), justify="right"),sep="\t", quote=FALSE, - row.names=T, col.names=T,file="Matrix.Data.tsv") - }else{ - colnames(data_matrix)<-designo$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$Package){ - suppressWarnings(suppressMessages(require("BiocManager", quietly = TRUE))) - suppressMessages(suppressWarnings(BiocManager::install(lbraries[!lbraries%in%installed$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 e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/Agilent_One_Color_Preprocessing.R --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/Agilent_One_Color_Preprocessing.R Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,90 +0,0 @@ -options(show.error.messages=F,warn=-1, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) -sink(stdout(), type = "message") -sink(stdout() ,type = "output") -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 -} - -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]]$E))), main="Boxplot of log2( intensities) before Background Correction",col="red",ylab="log2( intensities)",xlab="",las=2,mar=c(15,2,1,1)) -invisible(dev.off()) - -png(filename ="boxplot_after_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$E))), main="Boxplot of log2( intensities) After Background Correction",col="red",ylab="log2( intensities)",xlab="",las=2,mar=c(15,2,1,1)) -invisible(dev.off()) - -png(filename ="boxplot_after_NBA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNBA$E))), main="Boxplot of log2( intensities) After Normalization Between Arrays",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) -invisible(dev.off()) - -png(filename = "densities_plot_before_BG.png",width = w, height = h) -plotDensities(MicroArray_Object[[1]],log=T) -invisible(dev.off()) - -png(filename = "densities_plot_after_BG.png",width = w, height = h) -plotDensities(Prepro_object$dataBG,log=T) -invisible(dev.off()) - - -png(filename = "densities_plot_after_NBA.png",width = w, height = h) -plotDensities(Prepro_object$dataNBA,log=T) -invisible(dev.off()) - -OneColorRmd=file_path("OneColor.Rmd") -Style=file_path("look.css") -suppressWarnings(suppressMessages(knit2html(OneColorRmd,output="PreprocessingPlots.html",quiet = T))) -#suppressWarnings(suppressMessages(markdownToHTML(OneColorRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) -# suppressWarnings(suppressMessages(knit2html(OneColorRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) -rm(listArguments) -save.image("MicroArray.Preprocessing.RData") -sink() -sink() \ No newline at end of file diff -r e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/Agilent_One_Color_Preprocessing_Functions.R --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/Agilent_One_Color_Preprocessing_Functions.R Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,18 +0,0 @@ -AgilentOneColorPreprocessingFunction<- function(data,methodBC,methodNBA) -{ -MA <<- backgroundCorrect(data, method=methodBC ,offset = 2) -rownames(MA$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)),] -MAb$E=MAb$E[rownames(MAb$E) %in% MAb$genes$ProbeName,] -MA.avg <-suppressWarnings(suppressMessages(avereps(MAb, ID=rownames(MAb$E)))) -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$GeneName)) -} diff -r e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/Agilent_Two_Colors_Preprocessing.R --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/Agilent_Two_Colors_Preprocessing.R Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,122 +0,0 @@ -options(show.error.messages=F,warn=-1, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) -sink(stdout(), type = "message") -sink(stdout() ,type = "output") -suppressWarnings(suppressMessages(library(limma))) -suppressWarnings(suppressMessages(library(batch))) -suppressWarnings(suppressMessages(library(marray))) -suppressWarnings(suppressMessages(library(IDPmisc))) -suppressWarnings(suppressMessages(library(affy))) -suppressWarnings(suppressMessages(library(markdown))) -suppressWarnings(suppressMessages(library(knitr))) -source_local <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - source(paste(base_dir, fname, sep="/")) -} -file_path <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - pato <- paste(base_dir, fname, sep="/") - return(pato) -} -base_dir <- function(){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - return(base_dir) -} -source_local("Make_matrix_two_channels.R") -source_local("Agilent_Two_Colors_Preprocessing_Functions.R") -listArguments = parseCommandArgs(evaluate=FALSE) -print(listArguments) -# print(thefunction) -load(listArguments[["image"]]) -names(listArguments)[which(names(listArguments)=="image")]="data" -listArguments[["data"]]=MicroArray_Object$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$R)<-listcelsnames[-1] - -} - -png(filename ="boxplot_before_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$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]]$G))), main="Boxplot of log2(G intensities) before BGC",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -invisible(dev.off()) - -png(filename ="boxplot_after_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(Prepro_object$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$G))), main="Boxplot of log2(G intensities) After BGC",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -invisible(dev.off()) - -png(filename ="boxplot_after_NWA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(Prepro_object$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$G))), main="Boxplot of log2(G intensities) After NWA",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -invisible(dev.off()) - -png(filename ="boxplot_after_NBA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(RGNBA$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$G))), main="Boxplot of log2(G intensities) After NBA",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -invisible(dev.off()) - -png(filename ="MA_plot.png",width = w, height = h) -ma.plot(na.omit(Prepro_object$dataNBA$A), na.omit(Prepro_object$dataNBA$M), - show.statistics = F, span = 2/3, family.loess = "gaussian", - cex = 2, plot.method = as.character("smoothScatter"), - add.loess = TRUE, lwd = 1, lty = 1, loess.col = "red",main="MA plot") - -invisible(dev.off()) - -png(filename = "densities_plot_before_BG.png",width = w, height = h) -plotDensities(MicroArray_Object[[1]],log=T) -invisible(dev.off()) - -png(filename = "densities_plot_after_BG.png",width = w, height = h) -plotDensities(Prepro_object$dataBG,log=T) -invisible(dev.off()) - -png(filename = "densities_plot_after_NWA.png",width = w, height = h) -plotDensities(Prepro_object$dataNWA,log=T) -invisible(dev.off()) - -png(filename = "densities_plot_after_NBA.png",width = w, height = h) -plotDensities(Prepro_object$dataNBA,log=T) -invisible(dev.off()) - -TwoColorsRmd=file_path("TwoColors.Rmd") -Style=file_path("look.css") -#suppressWarnings(suppressMessages(markdownToHTML(TwoColorsRmd,output="PreprocessingPlots.html", stylesheet=Style))) -suppressWarnings(suppressMessages(knit2html(TwoColorsRmd,output="PreprocessingPlots.html",quiet = T))) -#suppressWarnings(suppressMessages(knit2html(TwoColorsRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) -rm(listArguments) -save.image("MicroArray.Preprocessing.RData") -sink() -sink() diff -r e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/Agilent_Two_Colors_Preprocessing_Functions.R --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/Agilent_Two_Colors_Preprocessing_Functions.R Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,21 +0,0 @@ -AgilentTwoChannelsPreprocessingFunction<- function(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$GeneName)) - Prepro_object1=make_design(MA_matrix=Prepro_object1) - return(Prepro_object1) -} diff -r e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/GenePix_One_Color_Preprocessing.R --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/GenePix_One_Color_Preprocessing.R Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,92 +0,0 @@ -options(show.error.messages=F,warn=-1, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) -sink(stdout(), type = "message") -sink(stdout() ,type = "output") -suppressWarnings(suppressMessages(library(limma))) -suppressWarnings(suppressMessages(library(marray))) -suppressWarnings(suppressMessages(library(batch))) -suppressWarnings(suppressMessages(library(IDPmisc))) -suppressWarnings(suppressMessages(library(markdown))) -suppressWarnings(suppressMessages(library(knitr))) -source_local <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - source(paste(base_dir, fname, sep="/")) -} -file_path <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - pato <- paste(base_dir, fname, sep="/") - return(pato) -} -base_dir <- function(){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - return(base_dir) -} -source_local("GenePix_One_Color_Preprocessing_Functions.R") -listArguments = parseCommandArgs(evaluate=FALSE) -print(listArguments) -load(listArguments[["image"]]) -names(listArguments)[which(names(listArguments)=="image")]="data" -listArguments[["data"]]=MicroArray_Object$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# -} - -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]]$E))), main="Boxplot of log2( intensities) before Background Correction",col="red",ylab="log2( intensities)",xlab="",las=2,mar=c(15,2,1,1)) -invisible(dev.off()) - -png(filename ="boxplot_after_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataBG$E))), main="Boxplot of log2( intensities) After Background Correction",col="red",ylab="log2( intensities)",xlab="",las=2,mar=c(15,2,1,1)) -invisible(dev.off()) - - -png(filename ="boxplot_after_NBA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -boxplot(log2(na.omit(as.data.frame(Prepro_object$dataNBA$E))), main="Boxplot of log2( intensities) After Normalization Between Arrays",col="red",ylab="log2(R intensities)",xlab="",las=2,mar=c(15,2,1,1)) -invisible(dev.off()) - -png(filename = "densities_plot_before_BG.png",width = w, height = h) -plotDensities(MicroArray_Object[[1]],log=T) -invisible(dev.off()) - -png(filename = "densities_plot_after_BG.png",width = w, height = h) -plotDensities(Prepro_object$dataBG,log=T) -invisible(dev.off()) - - -png(filename = "densities_plot_after_NBA.png",width = w, height = h) -plotDensities(Prepro_object$dataNBA,log=T) -invisible(dev.off()) - -OneColorRmd=file_path("OneColor.Rmd") -Style=file_path("look.css") -suppressWarnings(suppressMessages(knit2html(OneColorRmd,output="PreprocessingPlots.html",quiet = T))) -#suppressWarnings(suppressMessages(markdownToHTML(OneColorRmd,output="PreprocessingPlots.html", stylesheet=Style))) -#suppressWarnings(suppressMessages(knit2html(OneColorRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) -rm(listArguments) -save.image("MicroArray.Preprocessing.RData") -sink() -sink() \ No newline at end of file diff -r e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/GenePix_One_Color_Preprocessing_Functions.R --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/GenePix_One_Color_Preprocessing_Functions.R Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,17 +0,0 @@ -GenePixOneColorPreprocessingFunction<- function(data,methodBC,methodNBA) -{ - MA <<- suppressWarnings(suppressMessages(backgroundCorrect(data, method=methodBC ,offset = 16))) - rownames(MA$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$Name)) -} - diff -r e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/GenePix_Two_Colors_Preprocessing.R --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/GenePix_Two_Colors_Preprocessing.R Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,117 +0,0 @@ -options(show.error.messages=F,warn=-1, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) -sink(stdout(), type = "message") -sink(stdout() ,type = "output") -suppressWarnings(suppressMessages(library(limma))) -suppressWarnings(suppressMessages(library(marray))) -suppressWarnings(suppressMessages(library(batch))) -suppressWarnings(suppressMessages(library(IDPmisc))) -suppressWarnings(suppressMessages(library(affy))) -suppressWarnings(suppressMessages(library(markdown))) -suppressWarnings(suppressMessages(library(knitr))) -source_local <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - source(paste(base_dir, fname, sep="/")) -} -file_path <- function(fname){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - pato <- paste(base_dir, fname, sep="/") - return(pato) -} -base_dir <- function(){ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - return(base_dir) -} -source_local("Make_matrix_two_channels.R") -source_local("GenePix_Two_Colors_Preprocessing_Functions.R") -listArguments = parseCommandArgs(evaluate=FALSE) -load(listArguments[["image"]]) -names(listArguments)[which(names(listArguments)=="image")]="data" -listArguments[["data"]]=MicroArray_Object$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$R)<-listcelsnames[-1] - -} - -png(filename ="boxplot_before_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(MicroArray_Object[[1]]$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]]$G))), main="Boxplot of log2(G intensities) before BGC",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -invisible(dev.off()) - -png(filename ="boxplot_after_BG.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(Prepro_object$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$G))), main="Boxplot of log2(G intensities) After BGC",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -invisible(dev.off()) - -png(filename ="boxplot_after_NWA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(Prepro_object$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$G))), main="Boxplot of log2(G intensities) After NWA",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -invisible(dev.off()) - -png(filename ="boxplot_after_NBA.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") -old.par <- par(mfrow=c(1, 2)) -boxplot(log2(na.omit(as.data.frame(RGNBA$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$G))), main="Boxplot of log2(G intensities) After NBA",col="green",ylab="log2(G intensities)",xlab="",las=2,mar=c(15,2,1,1)) -par(old.par) -invisible(dev.off()) - -png(filename ="MA_plot.png",width = w, height = h) -ma.plot(na.omit(Prepro_object$dataNBA$A), na.omit(Prepro_object$dataNBA$M), - show.statistics = F, span = 2/3, family.loess = "gaussian", - cex = 2, plot.method = as.character("smoothScatter"), - add.loess = TRUE, lwd = 1, lty = 1, loess.col = "red",main="MA plot") -invisible(dev.off()) - -png(filename = "densities_plot_before_BG.png",width = w, height = h) -plotDensities(MicroArray_Object[[1]],log=T) -invisible(dev.off()) - -png(filename = "densities_plot_after_BG.png",width = w, height = h) -plotDensities(Prepro_object$dataBG,log=T) -invisible(dev.off()) - -png(filename = "densities_plot_after_NWA.png",width = w, height = h) -plotDensities(Prepro_object$dataNWA,log=T) -invisible(dev.off()) - -png(filename = "densities_plot_after_NBA.png",width = w, height = h) -plotDensities(Prepro_object$dataNBA,log=T) -invisible(dev.off()) - -TwoColorsRmd=file_path("TwoColors.Rmd") -Style=file_path("look.css") -#suppressWarnings(suppressMessages(markdownToHTML(TwoColorsRmd,output="PreprocessingPlots.html", stylesheet=Style))) -suppressWarnings(suppressMessages(knit2html(TwoColorsRmd,output="PreprocessingPlots.html",quiet = T))) -#suppressWarnings(suppressMessages(knit2html(TwoColorsRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style))) -rm(listArguments) -save.image(file="MicroArray.Preprocessing.RData") -sink() -sink() \ No newline at end of file diff -r e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/GenePix_Two_Colors_Preprocessing_Functions.R --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/GenePix_Two_Colors_Preprocessing_Functions.R Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,21 +0,0 @@ -GenePixTwoChannelsPreprocessingFunction<- function(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$Name))) -} - diff -r e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/Make_matrix_two_channels.R --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/Make_matrix_two_channels.R Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,28 +0,0 @@ -make_design<-function(MA_matrix){ - matrix<-RG.MA(MA_matrix$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 e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/OneColor.Rmd --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/OneColor.Rmd Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,370 +0,0 @@ - - - Preprocessing Plots Before and After - - - -
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Preprocessing

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

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- - diff -r e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/Preprocess_DataSet.xml --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/Preprocess_DataSet.xml Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,303 +0,0 @@ - - Preprocessing microarrays datasets.Contains Background Correction, Normalization within arrays, between arrays (depending on the number of channels) and summarization. - - citations.xml - - - r-biocmanager - pandoc - 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 e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/TwoColors.Rmd --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/TwoColors.Rmd Sat Dec 16 12:28:07 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,387 +0,0 @@ - - - Preprocessing Plots Before and After - - - -
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Preprocessing

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

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Used methods for each step

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method : `r listArguments[["methodBC"]]`
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- - diff -r e80d3d455db7 -r 4f7fbd73a770 preprocess_datasets/preprocess_datasets/preprocess_datasets/citations.xml --- a/preprocess_datasets/preprocess_datasets/preprocess_datasets/citations.xml Sat Dec 16 12:28:07 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. 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