[BioC] Nonorthogonal multiple comparisons in Limma/ Books on Bayesian Statistics

[Gordon Smyth]

At 11:36 PM 6/08/2004, Richard Friedman wrote:
>Gordon,
>
>         Thank you for answering my questions. The last equation in your 
> paper makes intuitive sense to me.
>
>         I'm wondering if you can take the time to answer two  more questions:
>
>1. Say I have the following case:
>
>Level A (3 replicates)
>Level B (2 replicates)
>Level C(1 replicate)
>Level D(1 replicate)
>
>Can I legitimately calculate a P value for the contrast Level A to level C 
>in the linear model even though I have only one replicate on Level C. I am 
>not talking about just Limma here. I am talking about the linear model in 
>general.

Given assumption of common variance across levels, yes.

>  Also,
>I realize that one replicate is poor experimental design. This is what I 
>was given to analyze.
>
>2. If I wished to apply a multiple test correction to the pvalues from 
>non-orthogonal contrasts, would the following procedure be legitimate::
>
>         1. Generate a pvalue for each contrast in the set of nonothogonal 
> contrasts for each gene  using classifyTestsF().
>         2. Correct the pvalues using a multiple test correction such as FDR.

Nothing special about this design. All usual things, e.g. in limma, apply.

Gordon

>I realize that no multiple-test correction is entirely satisfactory, I 
>just want to get an approximate estimate of the p-values for each contrast 
>as a guide to further experimentation and literature searching.
>
>Best wishes,
>Rich