Dear All,


I am using edgeR for an RNASeq experiment (~30 samples), where I need to
explore the influence of 2 factors with 2 levels each (there are actually
more factors, but for simplicity I put only 2 here):

1. disease_state (levels: control_0 and control_1)

2. localization (levels: A and B)


 I combined the factors and got 4 combinations:

control_0.localization_A, control_1.localization_A,
control_0.localization_B, control_1.localization_B.

I am specifically interested in a list of diff. expressed genes between
these 2 combinations: control_1.localization_A – control_1.localization_B.

When separating up- and down-regulated genes, I did it simply according to
logFC column (after filtering for genes with padj < 0.05). If the logFC<0,
could I infer that the gene is DOWN-regulated in control_1.localization_A?
I assume that this is true.

However, when I take the raw counts for one of the diff. expressed genes
(for which logFC<0), in control_1.localization_A and in
control_1.localization_B conditions, it turned out to be the following:

mean(control_1.localization_A) / mean(control_1.localization_B) = 4.2

(Formula explained in words: mean of raw counts for the diff. expressed
gene X in samples which are control_1 and localization_A, divided by mean
of raw counts for the diff. expressed gene X in samples which are control_1
and localization_B)

 This is contrary to the conclusion I got from logFC, since according to
raw counts that gene is UP-regulated in control_1.localization_A.

 I know that logFC is calculated differently, but shouldn't the ratio
(whether the gene is up- or down-regulated) stay nevertheless the same (if
library sizes are very similar in all samples, which is the case here)?

Maybe a more precise question would be: how is logFC calculated in this
case, when we have a combination of different factors?

Thank you very much in advance for any piece of clarification!

Mike

	[[alternative HTML version deleted]]

