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