[BioC] Making three-way and four-way comparisons
Ryan C. Thompson
rct at thompsonclan.org
Thu Apr 10 20:05:53 CEST 2014
Are you looking for genes that have any difference at all between any of
the three populations, or are you looking specifically for genes that
are different in *both* the A vs B and A vs C comparisons? For the
former case, you can pass multiple coefficients or contrasts to the
testing functions (glmLRT or glmQLFTest) to perform an ANOVA-like test.
For the latter, you should probably adapt the approach recommended by
Grodon Smyth in a recent thread on this list. Specifically, perform
each test separately and take the intersection of significant genes.
On 04/10/2014 07:31 AM, Maria [guest] wrote:
> 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?
> -- output of sessionInfo():
> R version 3.0.1 (2013-05-16)
> Platform: x86_64-w64-mingw32/x64 (64-bit)
>  LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
>  LC_MONETARY=English_United States.1252 LC_NUMERIC=C
>  LC_TIME=English_United States.1252
> attached base packages:
>  splines parallel stats graphics grDevices utils datasets methods base
> other attached packages:
>  edgeR_3.2.4 limma_3.16.8 DESeq2_1.0.19 RcppArmadillo_0.4.200.0
>  Rcpp_0.11.1 GenomicRanges_1.12.5 IRanges_1.18.4 pasilla_0.2.16
>  DESeq_1.12.1 lattice_0.20-29 locfit_1.5-9.1 DEXSeq_1.6.0
>  Biobase_2.20.1 BiocGenerics_0.6.0 BiocInstaller_1.10.4
> loaded via a namespace (and not attached):
>  annotate_1.38.0 AnnotationDbi_1.22.6 biomaRt_2.16.0 Biostrings_2.28.0 bitops_1.0-6
>  DBI_0.2-7 genefilter_1.42.0 geneplotter_1.38.0 grid_3.0.1 hwriter_1.3
>  RColorBrewer_1.0-5 RCurl_1.95-4.1 Rsamtools_1.12.4 RSQLite_0.11.4 statmod_1.4.18
>  stats4_3.0.1 stringr_0.6.2 survival_2.37-7 tools_3.0.1 XML_3.98-1.1
>  xtable_1.7-3 zlibbioc_1.6.0
> Sent via the guest posting facility at bioconductor.org.
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