I'm currently struggling with some DEseq2 analyses of RNA-seq data. I'm told this should be pretty 'easy' and just follow the vignette, but I'm finding some difficulties.
My situation is that everything seems to be working. I'm coming from this raw counts for a gene:
A_1: 900 A_2: 134 B_1: 14825 B_2: 8312
These are the normalized counts:
A_1: 784.8627 A_2: 203.5322 B_1: 19424.8883 B_2: 4966.5403
The sample table includes condition (A,A,B,B) and replicate (1,1,2,2). The design has been:
design = ~ condition + replicate
And the results have been obtained with:
How is it possible that for the gene with the counts above, I'm getting a positive log2FoldChange? When it should be more highly expressed in condition B according to the counts?
log2 fold change (MLE): condition A vs B Wald test p-value: condition A vs B baseMean: 6344.96 log2FoldChange: 1.95771 lfcSE: 0.373301 stat: 5.2443 pvalue: 1.56873e-07 padj: 2.76881e-05
I must be missing something. Can anyone point me to the right direction or to some documentation apart from the vignette? I'm aware the replicates are showing variability (they're far in the PCA). Could that be causing this?
Thank you very much for the help