[BioC] DESeq: Hypothesis testing in multifactor design

Michael Love michaelisaiahlove at gmail.com
Tue Jun 10 22:07:59 CEST 2014

hi Yanzhu,

Note that we recommend users switch to using DESeq2, which also has
the likelihood ratio test you are using, and is faster and more

The pipeline would look like:

DESeq(dds, test="LRT", reduced=~ A+B+C+A:B+A:C+B:C)

for your first example.

For your question, the terms of the reduced model should be contained
within the full model. Still there are a number of models which
satisfy this requirement, e.g. for testing B:C, you could use
A+B+C+A:B+A:C+B:C and A+B+C+A:B+A:C as full and reduced respectively.
Or you could use A+B+C+B:C and A+B+C. The importance of these other
interaction terms depends on context, whether they are very
explanatory or not.


On Tue, Jun 10, 2014 at 11:21 AM, yanzhu [guest] <guest at bioconductor.org> wrote:
> 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?
> Best,
> Yanzhu
>  -- output of sessionInfo():
> sessionInfo()
> R version 3.1.0 (2014-04-10)
> Platform: x86_64-w64-mingw32/x64 (64-bit)
> locale:
> [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
> --
> Sent via the guest posting facility at bioconductor.org.
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