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library(GEOquery) | ||
library(limma) | ||
GSE70529 <- getGEO('GSE70529', destdir=".",getGPL = F) | ||
exprSet=exprs(GSE70529[[1]]) | ||
library("annotate") | ||
GSE70529[[1]] | ||
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platformDB='hugene10sttranscriptcluster.db' | ||
library(platformDB, character.only=TRUE) | ||
probeset <- featureNames(GSE70529[[1]]) | ||
#EGID <- as.numeric(lookUp(probeset, platformDB, "ENTREZID")) | ||
SYMBOL <- lookUp(probeset, platformDB, "SYMBOL") | ||
a=cbind(SYMBOL,exprSet) | ||
## remove the duplicated probeset | ||
rmDupID <-function(a=matrix(c(1,1:5,2,2:6,2,3:7),ncol=6)){ | ||
exprSet=a[,-1] | ||
rowMeans=apply(exprSet,1,function(x) mean(as.numeric(x),na.rm=T)) | ||
a=a[order(rowMeans,decreasing=T),] | ||
exprSet=a[!duplicated(a[,1]),] | ||
# | ||
exprSet=exprSet[!is.na(exprSet[,1]),] | ||
rownames(exprSet)=exprSet[,1] | ||
exprSet=exprSet[,-1] | ||
return(exprSet) | ||
} | ||
exprSet=rmDupID(a) | ||
rn=rownames(exprSet) | ||
exprSet=apply(exprSet,2,as.numeric) | ||
rownames(exprSet)=rn | ||
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#exprSet=log(exprSet) | ||
#boxplot(exprSet,las=2) | ||
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pdata=pData(GSE70529[[1]]) | ||
## check the metadat and find the correct group information | ||
# we must tell R that group should be interpreted as a factor ! | ||
individuals=factor(unlist(lapply(pdata$title,function(x) strsplit(as.character(x),"-")[[1]][1]))) | ||
treatment=unlist(lapply(pdata$title,function(x) strsplit(as.character(x),"-")[[1]][2])) | ||
treatment=factor(sub('2','',treatment)) | ||
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## if only take the treatment into accont | ||
design=model.matrix(~treatment) | ||
fit=lmFit(exprSet,design) | ||
fit=eBayes(fit) | ||
#vennDiagram(fit,include=c("up","down")) | ||
write.csv(topTable(fit,coef='treatmentB',n=Inf,adjust='BH'),"treatmentBvsA.DEG.csv") | ||
write.csv(topTable(fit,coef='treatmentC',n=Inf,adjust='BH'),"treatmentCvsA.DEG.csv") | ||
write.csv(topTable(fit,coef='treatmentD',n=Inf,adjust='BH'),"treatmentDvsA.DEG.csv") | ||
## and we don't care about the difference between individuals | ||
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