Hi Steve,

I'm running the same analysis on both datasets (the larger and the
smaller). When I rerun the analysis on the smaller dataset (which actually
IS half of the identities from the larger data set), I come across an error
message when estimating glm trended dispersion. Here are the commands I'm
using:

> rawdata<-read.delim("piRNAtotalcount>10.txt", check.names=FALSE,
stringsAsFactors=FALSE)
> y <- DGEList(counts=rawdata[,2:11], genes=rawdata[,1])
> Family<-factor(c(6,6,9,9,11,11,26,26,28,28))
> Treatment<-factor(c("C","H","C","H","C","H","C","H","C","H"))
> data.frame(Sample=colnames(y),Family,Treatment)
   Sample Family Treatment
1      6C      6         C
2      6H      6         H
3      9C      9         C
4      9H      9         H
5     11C     11         C
6     11H     11         H
7     26C     26         C
8     26H     26         H
9     28C     28         C
10    28H     28         H
> design<-model.matrix(~Family+Treatment)
> rownames(design)<-colnames(y)
> y<-estimateGLMTrendedDisp(y,design)
Error in optim(par0, fun, y = y.nonzero[i, ], design = design, offset =
offset.nonzero[i,  :
      function cannot be evaluated at initial parameters

I only encounter this error when running the smaller dataset.

Best,
Eleanor



On Wed, Apr 2, 2014 at 9:49 AM, Steve Lianoglou <lianoglou.steve@gene.com>wrote:

> Hi Eleanor,
>
> On Tue, Apr 1, 2014 at 11:09 AM, Eleanor Su <eleanorjinsu@gmail.com>
> wrote:
> > Hi All,
> >
> > I'm currently trying to analyze differential expression of piRNAs in some
> > small data sets but am coming across issues that I didn't before when I
> > analyzed with a larger data set. The larger data set contained 324 piRNA
> > identities while the smaller data set contained half as many piRNA
> > identities. Is there a minimum number of gene identities required in
> order
> > to analyze differential expression in edgeR?
>
> It's hard to help without knowing what the issues are that you are
> running into, so ... what's going wrong?
>
> One way you could explore this question yourself is to use the larger
> (324 piRNA) dataset that "went well" and simply take half of the data
> from it and rerun the same analysis on the smaller set. Do you get
> different results?
>
> While you're playing with that idea, please provide a follow up email
> with more specific details about what the issues are that you are
> running into with your new (smaller) dataset.
>
> HTH,
> -steve
>
> --
> Steve Lianoglou
> Computational Biologist
> Genentech
>

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