0
+ − 1 options(show.error.messages=F, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)})
+ − 2 sink(stdout(), type = "message")
+ − 3 suppressWarnings(suppressMessages(library(affy)))
+ − 4 suppressWarnings(suppressMessages(library(affyPLM)))
+ − 5 suppressWarnings(suppressMessages(library(batch)))
+ − 6 suppressWarnings(suppressMessages(library(annotate)))
+ − 7 suppressWarnings(suppressMessages(library(limma)))
+ − 8 suppressWarnings(suppressMessages(library(markdown)))
+ − 9 suppressWarnings(suppressMessages(library(knitr)))
+ − 10 source_local <- function(fname){
+ − 11 argv <- commandArgs(trailingOnly = FALSE)
+ − 12 base_dir <- dirname(substring(argv[grep("--file=", argv)], 8))
+ − 13 source(paste(base_dir, fname, sep="/"))
+ − 14 }
+ − 15 file_path <- function(fname){
+ − 16 argv <- commandArgs(trailingOnly = FALSE)
+ − 17 base_dir <- dirname(substring(argv[grep("--file=", argv)], 8))
+ − 18 pato <- paste(base_dir, fname, sep="/")
+ − 19 return(pato)
+ − 20 }
+ − 21 base_dir <- function(){
+ − 22 argv <- commandArgs(trailingOnly = FALSE)
+ − 23 base_dir <- dirname(substring(argv[grep("--file=", argv)], 8))
+ − 24 return(base_dir)
+ − 25 }
+ − 26 source_local("Affymetrix_Preprocessing_Functions.R")
+ − 27 listArguments = parseCommandArgs(evaluate=FALSE)
+ − 28 thefunctions=listArguments[["thefunctions"]]
+ − 29 listArguments[["thefunctions"]]=NULL
+ − 30 h=listArguments[["h"]]
+ − 31 listArguments[["h"]]=NULL
+ − 32 w=listArguments[["w"]]
+ − 33 listArguments[["w"]]=NULL
+ − 34 if (!is.null(listArguments[["image"]])){
+ − 35 load(listArguments[["image"]])
+ − 36 listArguments[["image"]]=NULL
+ − 37 }
+ − 38 listArguments[["rawdata"]]=MicroArray_Object$affy_object
+ − 39 if(datasetsource=="intern"){
+ − 40 designo<-MicroArray_Object$designo
+ − 41 }
+ − 42
+ − 43 if(datasetsource=="extern"){
+ − 44 listArguments<-append(listArguments,list(datasetsource=datasetsource,listfullnames=listfullnames))
+ − 45 }
+ − 46 Prepro_object<-do.call(thefunctions,listArguments)
+ − 47 if(datasetsource=="extern"){
+ − 48 rownames(Prepro_object$data.bg@phenoData@data)<-listfullnames
+ − 49 colnames(exprs(Prepro_object$data.bg))<-listfullnames
+ − 50 colnames(exprs(Prepro_object$data.sm))<-listfullnames
+ − 51 colnames(exprs(Prepro_object$data.norm))<-listfullnames
+ − 52 colnames(exprs(Prepro_object$data.bg))<-listfullnames
+ − 53 colnames(exprs(Prepro_object$data.norm))<-listfullnames
+ − 54 rownames(Prepro_object$data.norm@phenoData@data)<-listfullnames
+ − 55 rownames(Prepro_object$data.norm@protocolData@data)<-listfullnames
+ − 56 }
+ − 57 par(las=2,mar=c(15,2,1,1))
+ − 58 png(filename ="boxplot_before_NM.png",width = w, height = h, units = "px", pointsize = 14, bg = "white")
+ − 59 par(las=2,mar=c(15,2,1,1))
+ − 60 boxplot((na.omit(as.data.frame(exprs(Prepro_object$data.bg)))), main="Boxplot of intensities before Normalization",col="red",las=2,mar=c(15,2,1,1))
+ − 61
+ − 62 dev.off()
+ − 63
+ − 64
+ − 65
+ − 66 par(las=2,mar=c(15,2,1,1))
+ − 67 png(filename ="boxplot_after_NM.png",width = w, height = h, units = "px", pointsize = 14, bg = "white")
+ − 68 par(las=2,mar=c(15,2,1,1))
+ − 69 boxplot((na.omit(as.data.frame(exprs(Prepro_object$data.sm)))), main="Boxplot of intensities After Normalization",col="red",ylab="(intensities)",las=2,mar=c(15,2,1,1))
+ − 70
+ − 71 dev.off()
+ − 72 png(filename ="MA_plot.png",width = w, height = h)
+ − 73 MAplot((Prepro_object$data.norm) ,
+ − 74 show.statistics = F, span = 2/3, family.loess = "gaussian",
+ − 75 cex = 2, plot.method = as.character("smoothScatter"),
+ − 76 azdd.loess = TRUE, lwd = 1, lty = 1, loess.col = "red")
+ − 77
+ − 78 dev.off()
+ − 79 png(filename = "densities_plot_before_NM.png",width = w, height = h)
+ − 80 plotDensities(exprs(Prepro_object$data.bg),log=T)
+ − 81 dev.off()
+ − 82
+ − 83 png(filename = "densities_plot_after_NM.png",width = w, height = h)
+ − 84 plotDensities(exprs(Prepro_object$data.norm),log=T)
+ − 85 dev.off()
+ − 86 AffymetrixRmd=file_path("Affymetrix.Rmd")
+ − 87 Style=file_path("look.css")
+ − 88 suppressWarnings(suppressMessages(knit2html(AffymetrixRmd,output="PreprocessingPlots.html",quiet = T, stylesheet=Style)))
+ − 89 rm(listArguments)
+ − 90 save.image("MicroArray.Preprocessing.RData")
