Hi Fatemehsadat,

I`m no expert in R, there may be a more elegant solution.
 Try this, I haven't tested, so minor modifications may be required.

tp <- topTags(lrt, n=15) # Extract the top 15 genes
de_counts<-dge$counts[row.names(tp), order(dge$samples$group)] # Get raw
counts for top genes
rs<-rowSums(de_counts) # Assuming by high count, across all samples
top.names <- names( rs[ order( rs, decreasing=TRUE ) ] )
de_counts[top.names, ] # DE genes Ranked ,highest first

Thanks,
Shreyartha


On Wed, Dec 12, 2012 at 7:22 AM, Fatemehsadat Seyednasrollah
<fatsey@utu.fi>wrote:

> Hi,
>
> For an RNA-seq data, I have found the significant DE genes based on FDR <
> 0.05 using the exactTest() function.
> Now I need to rank these DE genes based on the expression level (count
> values). What is the correct way of doing it?
>
> Thank you in advance.
>
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