[BioC] DESeq: Hypothesis testing in multifactor design

[Michael Love]

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
sensitive.

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.

Mike

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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