How to extract list of DE genes after EdgeR? With summary() I get number of Up and Down expressed genes. And I would like to extract the gene IDs for Up and Down. As I read from other manuals, the common way is to use filtering $table$logFC > 0 for up and $table$logFC < 0 for down regulated after applying TopTags() (see My pipeline). If I use this way with I get the same amount of DE genes as with summary().
But I did not understand why we use this way. Why we dont use filtering $table$logFC >1.5 for up and $table$logFC <1.5 for down if we use LogFC cutoff 1.5?
My pipeline: # filtering keep <- filterByExpr(y, design) y_filtered <- y[keep, , keep.lib.sizes=FALSE] # to estimate dispersion y_disp_design <- estimateDisp(y_filtered, design = design, verbose=TRUE) # Fit a quasi-likelihood negative binomial generalized log-linear model to count data fit <- glmQLFit(y_disp_design, design, robust = TRUE) # Conduct genewise statistical tests LFC <- 1.5 tr.c1_2 <- glmTreat (fit, contrast = my.contrasts[, 'c1_2'], lfc = log2(LFC)) # Identify which genes are significantly differentially expressed is.de.tr.c1_2 <- decideTestsDGE(tr.c1_2) # View the amount of Up and Down genes summary(is.de.tr.c1_2) Down 3191 NotSig 13930 Up 1077 # Extracts the most differentially expressed genes TT_tr.c1_2 <- topTags(tr.c1_2, Inf) # View TT_tr.c1_2 TT_tr.c1_2 Coefficient: 1*stage_1 -1*stage_2 logFC unshrunk.logFC logCPM PValue FDR TRINITY_DN583_c0_g1 -3.254507 -3.255309e+00 6.980710 1.123231e-11 2.044055e-07 TRINITY_DN1301_c4_g1 -5.887508 -5.921260e+00 3.852718 2.272249e-11 2.067519e-07 ... # extract Up genes up_c1_2 <- row.names(TT_tr.c1_2$table[TT_tr.c1_2$table$FDR < 0.05 & TT_tr.c1_2$table$logFC > 0, ]) length(up_c1_2) 1077