A professor sent me a bunch of raw RNA-seq reads (as FASTQ files) and I want
to align them, and I couldn't really make heads or tails of the options, so
I listened to what Phil Green told me at a conference and looked around for
a sensible word-nucleated aligner like he described.  It seems that Rsubread
works this way?

http://sourceforge.net/projects/subread/

I would like BAM files as intermediate output, but my real interest is
differential exon usage in differentiating cells.  Given that the reads I
have to align are relatively short (36bp, SE), is there an advantage or
disadvantage in using subread compared to other options?  And when I'm done
trimming and aligning, I could choose raw counts, conditional quantile
normalized counts, or something like RPKM to summarize how often a given
exon seems to have been transcribed.  I read this:

http://seqanswers.com/forums/showthread.php?t=586

and I see that packages using a Gamma prior for the dispersion of a Poisson
count model benefit from having raw counts.  If I am after correlated
changes in exon usage depending on other sequence features, is it reasonable
to use (say) 'cqn' on the raw counts, then log-transform and work with those
normalized counts?

Thanks for any suggestions,

-- 
Tim Triche, Jr.
USC Biostatistics

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