[BioC] Using fRMA with "alternative" CDF files

[Matthew McCall]

Adam,

Try using the default frma() function -- it performs almost the same
as the "random_effect" summarization and doesn't require a matrix
inversion (what is causing the error). The alternative CDFs contain
some probesets with far fewer probes (sometimes just 1 or 2 probes),
which can cause problems with the "random_effect" summarization
method.

Best,
Matt

On Tue, Jan 15, 2013 at 2:43 PM, Cornwell, Adam
<Adam_Cornwell at urmc.rochester.edu> wrote:
> Matt,
>
> Here's what I had for those steps- for both datasets
> arrayData.human <- ReadAffy(filenames = file.path(path,  humanFilenames), verbose = TRUE,  cdfname = HGU133Plus2_Hs_ENTREZG")
> arrayData.mouse <- ReadAffy(filenames = file.path(path,   mouseFilenames), verbose = TRUE, cdfname = "Mouse4302_Mm_ENTREZG")
>
> arrayData.human.frma <- frma(arrayData.human, summarize="random_effect")
> arrayData.mouse.frma <- frma(arrayData.mouse, summarize="random_effect")
>
> I also tried running just the mouse normalization, with the same result. There are six mouse samples, and it's not running out of memory. The normalization of the human data completes without error. If use the stock CDF for the mouse arrays, fRMA  runs fine.  I tried removing and reinstalling the mouse4302mmentrezgcdf package, but got the same thing.
>
> Thanks for the help,
> Adam Cornwell
>
> -----Original Message-----
> From: Matthew McCall [mailto:mccallm at gmail.com]
> Sent: Friday, January 04, 2013 2:47 PM
> To: Cornwell, Adam
> Cc: bioconductor at r-project.org
> Subject: Re: [BioC] Using fRMA with "alternative" CDF files
>
> Adam,
>
> The entrez gene alternative cdf is supported for the mouse4302 array, so it should work.
>
> Can you send me the commands you ran? Something like:
> obj <- ReadAffy()
> eset <- frma(obj)
>
> Best,
> Matt
>
> On Thu, Jan 3, 2013 at 4:30 PM, Cornwell, Adam <Adam_Cornwell at urmc.rochester.edu> wrote:
>> Hello,
>>
>> I'm trying to using fRMA on a set of human u133+ 2.0 arrays and a set
>> of mouse 430 2.0 arrays. Lately I've been using the BrainArray Entrezgene-derived CDFs in normalization. With the human dataset, I have no issues using the alternative CDF with fRMA, but with the mouse 430 2.0 arrays I get "Error in solve.default(xtx, xty) :
>>   system is computationally singular: reciprocal condition number = 0"
>> When I use the default CDF (by not specifying a CDF when loading in with ReadAffy()) fRMA works fine, so it seems like the issue is with the fRMA and the alternative CDF. Is use of the alternative CDFs supported with fRMA?
>>
>> Thanks!
>> Adam Cornwell
>>
>>> sessionInfo()
>> R version 2.15.1 (2012-06-22)
>> Platform: x86_64-pc-mingw32/x64 (64-bit)
>>
>> locale:
>> [1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252
>> [4] LC_NUMERIC=C                           LC_TIME=English_United States.1252
>>
>> attached base packages:
>> [1] stats     graphics  grDevices utils     datasets  methods   base
>>
>> other attached packages:
>> [1] mouse4302cdf_2.11.0          mouse4302frmavecs_1.1.12     mouse4302mmentrezgcdf_16.0.0 AnnotationDbi_1.20.2
>> [5] affy_1.36.0                  frma_1.10.0                  Biobase_2.18.0               BiocGenerics_0.4.0
>>
>> loaded via a namespace (and not attached):
>> [1] affxparser_1.30.0     affyio_1.26.0         BiocInstaller_1.8.3   Biostrings_2.26.2     bit_1.1-9             codetools_0.2-8
>>  [7] DBI_0.2-5             ff_2.2-10             foreach_1.4.0         GenomicRanges_1.10.3  IRanges_1.16.3        iterators_1.0.6
>> [13] MASS_7.3-22           oligo_1.22.0          oligoClasses_1.20.0   parallel_2.15.1       preprocessCore_1.20.0 RSQLite_0.11.2
>> [19] splines_2.15.1        stats4_2.15.1         tools_2.15.1          zlibbioc_1.4.0
>>
>>         [[alternative HTML version deleted]]
>>
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>
>
>
> --
> Matthew N McCall, PhD
> 112 Arvine Heights
> Rochester, NY 14611
> Cell: 202-222-5880



-- 
Matthew N McCall, PhD
112 Arvine Heights
Rochester, NY 14611
Cell: 202-222-5880