On Mon, Oct 25, 2010 at 5:58 AM, Michael Dondrup <Michael.Dondrup@uni.no>wrote:

> Hi,
>
> I need some statistical advise for the following problem. Given an RNA-seq
> experiment I would like to assess
> statistical significance of differential read-counts >within< a sample.
> Given a sample with read counts
> for two (adjacent) regions out of all all regions of the genome I am
> interested in, say gene A and intron B.
>
>
Hi, Michael.

Comparing two different regions directly in the same sample is a problem
that introduces a few more sources of biological and technical variation
than comparing the same region between samples.  Assume that the number of
molecules for each of the two regions is identical in the cell.  First, the
mappability of the two regions could be quite different, leading to
differences in counts between the regions.  Second, the GC content or other
sequence-level characteristics of the two regions could be different,
leading to different efficiencies in the sequencing procedure, again leading
to differences in counts between regions.  Third, the structure of the
region in combination with an individual mapping method can also contribute
to differences in read counts between two regions.  There may be clever ways
to control for these issues, but I am not aware of fully general ways of
doing so.

Sean


> I wish to detect if region B has a significantly lower read count than A,
> lengths of regions A and B are known to be different,
> so I think fisher's-exact test does not apply here. Region length should be
> taken into account for this, as I think that
> the more positions are different between regions, the more significant the
> result should be. I also have biol. replicates,
> but these replicates have different numbers of reads.
>
> Packages like DEseq and edgeR seem to be tailored to between samples
> comparison. So which method
> would you recommend for within sample comparison?
>
> Thank you very much
> Michael
>
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