Dear all Hi
I worked on RNA-seq and microarray data before but now I am currently working on TMT labeled proteome data for the first time. My data achieved based on 5-time points (in days 0,1,3,6,12) and at any time point, I have data from two TMT 10-plex (two batches). So in any time point, for any TMT we have 2 replicates. As you know the range of TMT data is large and based on the last similar studies, I calculated log2 of data firstly. Then I normalized data by "scale" function and then removed the batch effect between two TMT runs by Combat (or removeBatchEffect from limma). After these steps, my data became ready to analyze. My questions are:
1- Am I right to use the limma package and "ebayes" function to find DEPs (differencial expressed proteins) between any specific time point to other time points?
2- If the answer of question 1 is yes, how can I write the "makeContrasts" function?
3- For Day3, when I put colnames=D3 for columns related to Day3 and put colnames=other for columns related to other time points and:
cont.matrix <- makeContrasts("D3-other",levels=design)
==> No DEPs can find.
when I put colnames=D3 for columns related to Day3, colnames=before for columns related to Day0 and Day1 and colnames=after for columns related to Day6 and Day12 :
cont.matrix <- makeContrasts("D3-befor","D3-after",levels=design) fit2 <- contrasts.fit(fit, cont.matrix) fit2 <- eBayes(fit2, 0.01) tT=topTable(fit2, adjust="BH", number=Inf) if (! is.null(ann)) tT <- cbind(tT, ann[as.numeric(rownames(tT)),,drop=F]) colnames(tT)[1:2] <- c("before","after") tT$logFC <- rowMeans(cbind(tT$before, tT$after), na.rm=TRUE) DEPs <- tT[tT$adj.P.Val<0.05,] DEPs$ABS_lofFC <- abs(DEPs$logFC) DEPs<- DEPs[DEPs$ABS_lofFC >1,]
==> I could find 646 DEPs.
4- Please note that at least 400 DEPs is obtained when the indipendent t-test is performed between the given time point data and the other time points data.
Gordon Smyth and other colleagues whats your idea? how can I design the contrast to find true DEPs?