[BioC] Extracting top upregulated genes from Limma analysis

[Noah Dowell]

Hello Casper,

This is from memory so double check it but the following should work:

results <- decideTests(fit2, method="global")
up <- which(results[,1] == 1)  
upGenes <- fit2[up, ]
upTable <- topTable(upGenes[,4], number = 50, adjust.method= "BH", sort.by="p")


The decideTests function assigns "upregulated" (actually DE genes in a positive direction) genes as "1" and "-1" for "downregulated" genes.

HTH,

noah

On Mar 1, 2011, at 9:41 PM, Casper Shyr wrote:

> 
> Hello,
>  I have my results after running a microarray analysis. In general, the analysis is basically comparing gene expressions in 1 tumor group to another.
>  Below are my relevant codes:
> 
> mm2 <- model.matrix(~TumorType, pData(eset2))
> fit2 <- lmFit(eset2, mm2)
> fit2 <- eBayes(fit2)
> 
>  Now I want to extract the top 50 up-regulated genes, but I am not sure how to do so. I know with toptable function, I can extract the top differentially expressed genes, but what if I only want the up-regulated ones? 
> 
> Thanks in advance!
> Sincerely,
> Casper
> 		 	   		  
> 	[[alternative HTML version deleted]]
> 
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