[BioC] Making three-way and four-way comparisons

Gordon K Smyth smyth at wehi.EDU.AU
Sat Apr 12 09:28:23 CEST 2014


> Date: Thu, 10 Apr 2014 07:31:13 -0700 (PDT)
> From: "Maria [guest]" <guest at bioconductor.org>
> To: bioconductor at r-project.org, maymay at gazeta.pl
> Subject: [BioC] Making three-way and four-way comparisons
>
>
> Hi all,
> I have read the entire edgeR user guide and some posts on here but I still do not understand if it possible to make non-pairwise contrasts in edgeR (or is it even an oxymoron)in the GLM mode. The only non-simple contrasts I could find are of the form (taken from the user guide):
> DrugvsPlacebo.2h = (Drug.2h-Drug.0h)-(Placebo.2h-Placebo.0h)
> but I have different setup.
>
> I have 3 different populations and I would like to see find genes that are significantly different between population A and B, and A and C simultaneously.
> Of course, I could make pairwise comparisons and look for intercept in DEG, but I am not sure it is the proper way?

Yes, that is the proper way.  Since you want two different null hypotheses 
to be rejected for the same genes, you must look at the AvsB and AvcC 
comparisons separately, and then overlap them.

Gordon

> Regards,
> Maria
>
> -- output of sessionInfo():
>
> R version 3.0.1 (2013-05-16)
> 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] splines   parallel  stats     graphics  grDevices utils     datasets  methods   base
>
> other attached packages:
> [1] edgeR_3.2.4             limma_3.16.8            DESeq2_1.0.19           RcppArmadillo_0.4.200.0
> [5] Rcpp_0.11.1             GenomicRanges_1.12.5    IRanges_1.18.4          pasilla_0.2.16
> [9] DESeq_1.12.1            lattice_0.20-29         locfit_1.5-9.1          DEXSeq_1.6.0
> [13] Biobase_2.20.1          BiocGenerics_0.6.0      BiocInstaller_1.10.4
>
> loaded via a namespace (and not attached):
> [1] annotate_1.38.0      AnnotationDbi_1.22.6 biomaRt_2.16.0       Biostrings_2.28.0    bitops_1.0-6
> [6] DBI_0.2-7            genefilter_1.42.0    geneplotter_1.38.0   grid_3.0.1           hwriter_1.3
> [11] RColorBrewer_1.0-5   RCurl_1.95-4.1       Rsamtools_1.12.4     RSQLite_0.11.4       statmod_1.4.18
> [16] stats4_3.0.1         stringr_0.6.2        survival_2.37-7      tools_3.0.1          XML_3.98-1.1
> [21] xtable_1.7-3         zlibbioc_1.6.0

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