problem with aveLogCPM.default in edgeR
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@suzystiegelmeyersyngentacom-5940
Last seen 6.6 years ago
United States
Hi, I recently upgraded edgeR from 3.0.8 to 3.2.3 and I'm noticing some differences. I have some data that I normalized with EDASeq. I attempted to calculate the trended dispersion and I get the following error: > dglmtrend=estimateGLMTrendedDisp(exprs(dataNormgcOff),design,offset= -offst(dataNormgcOff)) Error in t(y) + prior.count.scaled : non-conformable arrays > class(dataNormgcOff) [1] "SeqExpressionSet" attr(,"package") [1] "EDASeq" > dim(exprs(dataNormgcOff)) [1] 19062 36 > dim(offst(dataNormgcOff)) [1] 19062 36 The error seems to occur in the aveLogCPM.default function due to matrix addition on two matrices with differing dimensions. Line 34 reads as: abundance <- mglmOneGroup(t(t(y)+prior.count.scaled),dispersion=disper sion,offset=offset) I no longer get an error if I change it to: abundance <- mglmOneGroup(y+prior.count.scaled,dispersion=dispersion,offset=offset) I don't think this is the best solution to fix all scenarios since I don't know this code very well. So, I see some things have changed and I'm wondering if I need to make some changes in how I call the function or if there is really a bug of some kind here. Thanks in advance for your help, Suzy > sessionInfo() R version 3.0.0 (2013-04-03) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 [3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C [5] LC_TIME=English_United States.1252 attached base packages: [1] parallel stats graphics grDevices utils datasets methods base other attached packages: [1] EDASeq_1.6.0 aroma.light_1.30.1 matrixStats_0.8.1 ShortRead_1.18.0 [5] latticeExtra_0.6-24 RColorBrewer_1.0-5 Rsamtools_1.12.3 lattice_0.20-15 [9] Biostrings_2.28.0 GenomicRanges_1.12.3 IRanges_1.18.1 Biobase_2.20.0 [13] BiocGenerics_0.6.0 edgeR_3.2.3 limma_3.16.3 loaded via a namespace (and not attached): [1] annotate_1.38.0 AnnotationDbi_1.22.5 bitops_1.0-5 DBI_0.2-7 [5] DESeq_1.12.0 genefilter_1.42.0 geneplotter_1.38.0 grid_3.0.0 [9] hwriter_1.3 R.methodsS3_1.4.2 RSQLite_0.11.3 splines_3.0.0 [13] stats4_3.0.0 survival_2.37-4 tools_3.0.0 XML_3.96-1.1 [17] xtable_1.7-1 zlibbioc_1.6.0 _________________________________ Suzy Stiegelmeyer, PhD Computational Biologist Bioinformatics Syngenta Biotechnology, Inc. 3054 Cornwallis Rd Research Triangle Park, NC 27709 USA phone +1 919 281 7472 suzy.stiegelmeyer@syngenta.com<mailto:suzy.stiegelmeyer@syngenta.com> www.syngenta.com<http: www.syngenta.com=""/> This message may contain confidential information. If yo...{{dropped:7}}
edgeR EDASeq edgeR EDASeq • 798 views
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@gordon-smyth
Last seen 35 minutes ago
WEHI, Melbourne, Australia

You can avoid the problem by forming a DGEList:

   y <- DGEList(counts=exprs(dataNormgcOff))
   y$offset <- -offst(dataNormgcOff)

Then

   y <- estimateGLMCommonDisp(y, design)

etc.

Gordon

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