Mercurial > repos > proteomisc > preprocess_dataset
diff preprocess_datasets/Affymetrix_Preprocessing_Functions.R @ 0:ebf6607b4e6a draft
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author | proteomisc |
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date | Sat, 02 Dec 2023 14:15:26 +0000 |
parents | |
children | 4b3faf457c37 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/Affymetrix_Preprocessing_Functions.R Sat Dec 02 14:15:26 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)) + + }