Hello,
    I'm interested in calculating differential expression from some paired
RNAseq samples.

I've used htseq-count after mapping; quite happy with how easy that was.

My question is with regard to whether or not to trip the last five rows
from htseq-count output.

Those rows look like this:
no_feature 152030
ambiguous 4876
too_low_aQual 0
not_aligned 0
alignment_not_unique 0

I can dream of reasons supporting either side of this question.. The number
of unmapped or ambiguously-mapping reads do contribute to the total library
size.  However, I'm also interested in quantifying the difference between
what's human in both samples, so intuition would tell me to remove those
reads.

Because the counts are big, this matters a great deal.  I'm using EdgeR
(again, very happy with that software), and the manual cites htseq-count as
a  viable methodology, but doesn't comment on their preferred treatment of
the unmapped reads.

My first (somewhat careless) utilization of EdgeR gave us results that
appeared to make sense, but upon digging a little deeper, I noticed that
this question affects the p-values quite a lot because the unmapped counts
are so big.

I would appreciate any comments/opinions!

Thanks,
Jonathan

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