Hi

I am analyzing Affymetix data and have loaded the data, done gcrma, made the design matrix, lmFit, makeContrasts, contrasts.fit and eBayes. Now I would like to know which genes are differentially expressed and have a fold change >= +-2. 

I have used the following command to get an overview of the changing genes over all the contrasts:

desTest <- decideTests(fitContr2, adjust.method=”BH”, p.value = 0.01) 

This is a great function! But how can I get more information about the genes: p-values etc? I have tried to use topTable 

tilFil <- topTable(fitContr2, coef = 1, number= 100, adjust.method = “BH”)

but it is hard to get the same genes from the two functions (topTable and decideTest), and it is hard to find a good cut of for the number of genes to include in the topTable function.

Does any one have any suggestions?

When I use topTable I get different parameters and I am trying to understand what the different parameters can tell me but I am still confused about M and log-odds. (And yes I have read a lot of documentation and books, but no one seems to agree/explain it good enough for me to understand) 

Regards,
Ingrid :-)



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