[Bioc-sig-seq] error msg from edgeR estimateCRDisp

[Gordon K Smyth]

Dear Kirsten,

The error is arising in mglmOneGroup.  I have just updated the relevant, 
code in edgeR version 2.0.3.  Can you try it and see if you get the same 
error?

With regard to the warning message, I can't think of any reason why edgeR 
would evaluate the Poisson density at a non-integer value if you have 
provided integer values.  Have you checked that you have provided strictly 
integer counts?  Try

   data$counts <- round(data$counts)
   data.cd = estimateCRDisp(data, design)

to see if it makes any difference.  If it does, then the data you entered 
are not all integers.

We are planning to revise estimateCRDisp() quite a bit during the next 
month or so.

Best wishes
Gordon

> Date: Wed, 29 Dec 2010 15:39:01 -0500
> From: <kristen.dang at syngenta.com>
> To: <bioc-sig-sequencing at r-project.org>
> Subject: [Bioc-sig-seq] error msg from edgeR estimateCRDisp
>
> Dear fellow edgeR users,
>
> I have an RNA-seq dataset with 2 factors and 24 samples (balanced) that 
> I am attempting to analyze with edgeR. I keep encountering the following 
> error when I use the estimateCRDisp function.
>
>> data.cd = estimateCRDisp(data, design)
> Error in while (any(i)) { : missing value where TRUE/FALSE needed
> In addition: There were 50 or more warnings (use warnings() to see the first 50)
>> warnings()
> Warning messages:
> 1: In dpois(y[i, ], lambda = mu[i, ], log = TRUE) : non-integer x = 530.381844
> 2: In dpois(y[i, ], lambda = mu[i, ], log = TRUE) : non-integer x = 676.500000
> [etc]
>
>> traceback()
> 3: mglmOneGroup(y, offset, dispersion)
> 2: adjustedProfileLik(spline.disp[i], y.filt, design = design, offset = offset.mat.filt +
>       lib.size.mat.filt)
> 1: estimateCRDisp(data, design)
>>
>
> I see why the "dpois" function is giving an error, but I am not sure why 
> a non-integer value is being sent to it. Any suggestions are greatly 
> appreciated.
>
>
> Information about my session and commands follows:
>
> library(edgeR)
> targets = read.csv("design_file.csv")
> targets$factor_a = factor(targets$factor_a)
> targets$factor_b = factor(targets$factor_b)
>
> data = readDGE(targets)
> data = calcNormFactors(data)
>
> contrasts(targets$factor_a) = contr.sum(2)
> contrasts(targets$factor_b) = contr.sum(2)
> design = model.matrix(~factor_a+factor_b, data = targets)
> data.cd = estimateCRDisp(data, design)
>
>
>> sessionInfo()
> R version 2.12.0 (2010-10-15)
> Platform: i386-pc-mingw32/i386 (32-bit)
>
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base
>
> other attached packages:
> [1] edgeR_2.0.2
>
> loaded via a namespace (and not attached):
> [1] limma_3.6.9  tools_2.12.0
>
>
>
> Kristen Dang, Ph.D.
> Computational Biologist
> Syngenta Biotechnology
> Research Triangle Park, NC

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