problem with aveLogCPM.default in edgeR
1
0
Entering edit mode
@suzystiegelmeyersyngentacom-5940
Last seen 9.7 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 • 1.4k views
ADD COMMENT
0
Entering edit mode
@gordon-smyth
Last seen 1 minute 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

ADD COMMENT

Login before adding your answer.

Traffic: 509 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6