[BioC] edgeR - zero values

[James W. MacDonald]

Hi Laura,

See ?glmFit, particularly the prior.count artument:

prior.count: average prior count to be added to observation to shrink
          the estimated log-fold-changes towards zero.

and this part from the Details section:

Positive ‘prior.count’ cause the returned coefficients to be
     shrunk in such a way that fold-changes between the treatment
     conditions are decreased. In particular, infinite fold-changes are
     avoided. Larger values cause more shrinkage. The returned
     coefficients are affected but not the likelihood ratio tests or
     p-values.

Best,

Jim



On Friday, February 07, 2014 1:48:26 PM, Laura Eierman wrote:
> I am working with edgeR to look at differential expression in a 2x2 design
> of two populations with two treatments (a total of 4 groups with 6
> replicates each).  I have very interesting results. However, a colleague
> asked me the other day, "What does edgeR do with zero values for read count
> data?"
>
> I have an intermediate level of statistical understanding at best, and in
> some instances, a novice level.  I am assuming that the negative binomial
> model in some way accounts for tags with a large number of 0 cells.  Is
> there something more going on the generalized linear model or in fitting
> the negative binomial distribution that accounts for a large percentage of
> zeros from some of the tags?
>
> Thank you for your guidance!
>
> 	[[alternative HTML version deleted]]
>
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--
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
4225 Roosevelt Way NE, # 100
Seattle WA 98105-6099