[BioC] DESeq: Hypothesis testing in multifactor design

yanzhu [guest] guest at bioconductor.org
Tue Jun 10 17:21:46 CEST 2014

Dear Community,

I have a question about the hypothesis testing of the two-way interaction terms in a multifactor design which includes three factors: A, B and C.

When I tested the three-way interaction I used the full and reduced models as below for nbinomGLMTest():
Full: count ~ A+B+C+A:B+A:C+B:C+A:B:C
Reduced: count ~ A+B+C+A:B+A:C+B:C 

Now comes my question, when I want to test the effect of two-way interaction terms, i.e., A:B, A:C or B:C, what should be my full and reduced models? For example, when I want to the test the effect of A:B, what should be my full and reduced models for nbinomGLMTest() using DESeq pacakge?



 -- output of sessionInfo(): 

R version 3.1.0 (2014-04-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)

[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United States.1252    

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] DESeq_1.16.0        lattice_0.20-29     locfit_1.5-9.1      Biobase_2.24.0      BiocGenerics_0.10.0 edgeR_3.6.1         limma_3.20.1       

loaded via a namespace (and not attached):
 [1] annotate_1.42.0      AnnotationDbi_1.26.0 DBI_0.2-7            genefilter_1.46.0    geneplotter_1.42.0   GenomeInfoDb_1.0.2  
 [7] grid_3.1.0           IRanges_1.22.6       MASS_7.3-31          RColorBrewer_1.0-5   RSQLite_0.11.4       splines_3.1.0       
[13] stats4_3.1.0         survival_2.37-7      tools_3.1.0          XML_3.98-1.1         xtable_1.7-3        

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