[BioC] EdgeR multi-factors testing questions

Yanzhu [guest] guest at bioconductor.org
Mon Jan 27 14:16:13 CET 2014

Hi Gordon,

I have one more question about edgeR. I have used different normalization methods to normalize the data and then test the main effects, the two-way interaction terms and the three-way interaction term as we discussed before. To my surprise, the P-values results of the testings are the same for data normalized by TMM and Upper quartile. Is it possible?




Dear Yanzhu,

Yes, that's how I would do it.  Keep the same dispersions for all fits.

Best wishes

 -- output of sessionInfo(): 

> sessionInfo() 
R version 3.0.1 (2013-05-16)
Platform: x86_64-w64-mingw32/x64 (64-bit)

[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] DESeq_1.12.1       lattice_0.20-15    locfit_1.5-9.1     Biobase_2.20.1     BiocGenerics_0.6.0
[6] edgeR_3.2.4        limma_3.16.8      

loaded via a namespace (and not attached):
 [1] annotate_1.38.0      AnnotationDbi_1.22.6 DBI_0.2-7            genefilter_1.42.0   
 [5] geneplotter_1.38.0   grid_3.0.1           IRanges_1.18.4       RColorBrewer_1.0-5  
 [9] RSQLite_0.11.4       splines_3.0.1        stats4_3.0.1         survival_2.37-4     
[13] tools_3.0.1          XML_3.98-1.1         xtable_1.7-1        

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