[BioC] DESeq pairwise comparisons between conditions within a multi-factor design

[Simon Anders]

Hi Andrew

On 15/03/13 22:56, Andrew Lysaght wrote:
[...]
> fit1 <- nbinomFitGLM(cds, count ~ Blocking + Exposure )
> fit2 <- nbinomFitGLM(cds, count ~ Blocking + Exposure + Time)
> pvals <- nbinomGLMTest( fit2, fit1 )
>
> I am unclear whether the significant genes returned by this analysis are
> significant across all time points or any time point. Is there a way to
> test pairwise (time1 vs. time2) while preserving the blocking and exposure
> components (ie not using nbinomTest to directly compare time1 and time 2)

Significance with the test you use above means that you can reject the 
null hypothesis that expression does not change over time, i.e. that at 
least one time point is different.

To compare two specific time points, subset the cds object to the 
samples from these two time point before the test:

cds2 <- cds[ , pData(cds)$Time %in% c( "timepoint1", "timepoint2" ) ]

where "timepoint1" and "timepoint2" are the levels describing the two 
time points you want to compare.

Then run nbinomFitGLMs and nbinomGLMTest as above on cds2.

Unless noise (within-group variability) is very different in different 
time points, you get better power if you do the subsetting _after_ 
calling estimateDispersion.

   Simon