I'm facing serious problem trying to recalculate the results of a given Series from GEO. For better understanding I will just describe the experiment briefly
There are 22 samples, two samples are always a replicate. And the first two belong to the control group. I managed to calculate the mean value of each two replicates, logFC , the logratio in comparison to control and also the fold change. In order to find differential expressed genes (twofold up or down compared to control) that are common in at least 9 of 10 sample group I used LIMMA in R.
samples <- as.factor(samples) design <- model.matrix(~0 + samples) fit <- lmFit(exprSet, design) contrast.matrix <- makeContrasts(RF_control= control-RF, LNIT_control= control-LNIT, REC_control= control-REC, LIP_control=control-LIP, BUR_control= control-BUR,BRI_control=control-BRI, UL_control=control-UL, FF_control=control-FF, LT_control=control-LT, LTMAS_control= control-LTMAS, levels=design ) fits <- contrasts.fit(fit, contrast.matrix) eFit <- eBayes(fits) topTable(eFit, number=10, coef=1) nrow(topTable(eFit, coef=1, number=10000, lfc=2)) probeset.list <- topTable(eFit, coef=1, number=10000, lfc=2) gene.symbols <- getSYMBOL(rownames(probeset.list), "hgu133plus2") results <- cbind(probeset.list, gene.symbols) write.table(results, "results1.txt", sep="\t", quote=FALSE)
I compared the logFC generated by LIMMA of some genes with the logFC that i have calculated before(which are definitely right) and they are different. Is LIMMA used wrongly?
And how to I combine the different data from each coefficient, sind they result in different row numbers
Thank you very much!