Hello, I am trying to analyze affymetrix microarray data (GSE27157). I did differential gene expression analysis using limma and used topTable() function to extract the top genes. I wanted to extract the genes with adj.p.value < 0.05, however filtering with this criteria returns nothing. The smallest amount for adj.p.value is 0.4 !!. Is it normal or there is a problem in my analysis? I did RMA to normalize my data and also tried with GCRMA but both returned the same result. Could I extract based on p.value instead of adj.p.value, in this case (p.value < 0.05 and lfc = 2) it returns 111 genes.
design <- model.matrix(~0 + samples) colnames(design) <- c("Mut", "Wt") fit <- lmFit(eset2, design) contrast.matrix <- makeContrasts(Mut-Wt, levels = design) fit.con <- contrasts.fit(fit, contrast.matrix) fit.eb <- eBayes(fit.con) dge <- topTable(fit.eb, number = 1000, lfc = 2) dge[which(dge$P.Value < 0.05),] dim(dge[which(dge$P.Value < 0.05),])
any help would be great appreciated!!