edgeR in order to perform differential expression analysis from RNA-seq experiment.
I have 6 samples of tumor cell, same tumor and same treatment: 3 patient with good prognosis and 3 patient with bad prognosis. I want to compare the gene expression among the two groups.
I ran the
edgeR pakage like follow:
x <- read.delim("my_reads_count.txt", row.names="GENE") group <- factor(c(1,1,1,2,2,2)) y <- DGEList(counts=x,group=group) y <- calcNormFactors(y) y <- estimateCommonDisp(y) y <- estimateTagwiseDisp(y) et <- exactTest(y)
I obtained a very odd results: in some cases I had a very low p-value and FDR but looking at the raw data it is obvious that the difference between the two groups can't be significant.
This is an example for
GENE sample1_1 sample1_2 sample1_3 sample2_1 sample2_2 sample2_3 ENSG00000198842 0 3 2 2 6666 3 ENSG00000257017 3 3 25 2002 29080 4
GENE logFC logCPM PValue FDR ENSG00000198842 9.863211e+00 5.4879462930 5.368843e-07 1.953612e-04 ENSG00000257017 9.500927e+00 7.7139869397 8.072384e-10 7.171947e-07
I would like that the variance within the group is considered. Does anyone may help me? Some suggestion?