Hi All,

I am wondering if someone can explain when it is appropriate to use the nestedF method of the decideTests function in Limma? 

>From the manual I am aware that this adjusts down genes then across contrasts and that this strategy is recommended for complex experiments with many contrasts (like mine) since it may be "desirable to select genes firstly on the basis of their moderated F-statistic, and subsequently decide which of the individual contrasts are significant for the selected gene.

I am interested in identifying genes that are differentially expressed in many contrasts- in particular across genotypes that are fairly similar, across treatments, and in various genotype:treatment combinations (ie interaction effects). I expect that the genotype effect will alter the same genes for some of the samples. I also expect that the treatment effect will alter some of the same genes across all the genotypes.

Is this an appropriate situation in which to use a nestedF test (I will also correct for multiple testing using "BH")?
Is it correct to form a contrast matrix for all my contrasts of interest (including interaction effects) and test them all simultaneously using decideTests(x, method="nestedF", method.adjust="BH", p=0.05)?  

I have done so and as can be expected this returned a far larger number of DE genes (compared to decideTests(method = "separate", method.adjust="BH", p=0.05). In fact, the number of genes called significant by this approach for some of my contrasts is quite alot ~ 5,000/24,000  (only ~ 100 for others) and perahps more than I perhaps want use in for example other analyses such as GeneSet enrichment or GO analyses, or heat maps.

If I wish to only consider a smaller number of genes, is it more correct in a statistical sense to use a more stringent p-value cutoff after performing decideTests(x, method= "nestedF",  method.adjust="BH", p=0.0001) or to consider the contrasts separately and use a larger p-value cutoff?
Clearly, some of these tests are not independent, so I am inclined to go with the nestedF approach and a more stingent cutoff.

I have read through other postings, and found this one especially helpful:
 https://stat.ethz.ch/pipermail/bioconductor/2006-March/012182.html
 but am still uncertain about my approach. Any comments would be appreciated.

Thanks in advance, 
Noelle

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