Using fRMA with "alternative" CDF files
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@cornwell-adam-5680
Last seen 2.5 years ago
United States
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]]
Normalization cdf frma Normalization cdf frma • 998 views
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@matthew-mccall-4459
Last seen 2.4 years ago
United States
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]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- Matthew N McCall, PhD 112 Arvine Heights Rochester, NY 14611 Cell: 202-222-5880
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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@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]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor -- Matthew N McCall, PhD 112 Arvine Heights Rochester, NY 14611 Cell: 202-222-5880
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@matthew-mccall-4459
Last seen 2.4 years ago
United States
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]] >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor > > > > -- > 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
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