If I may chime in:

GSEA does work with pre-sorted gene lists; human gene names were required last time I looked.

I found ranking by fold-change alone not to be satisfactory for GSEA, as this ignores the statistics outcome of a differential expression test.
Ranking by (-log10(padj))*(log2(ratio)) works a bit better but still lets fold-change outliers (high fold-change but not significant) pass through.

I ended up constructing my ranked gene list in four parts:
1. Statistically significant (padj derived from either DESeq or edgeR), up-regulated ranked descending by fold change
2. Not significant, expression increased or no change, ranked ascending by p value
3. Not significant, expression decreased or no change, ranked descending by p value
4. Statistically significant, down-regulated, ranked descending by fold change

Not elegant, but somewhat workable; GSEA calls have to be scrutinized at the 1-2 and 3-4 boundary.

Cheers, michael

J. Michael Salbaum, Ph.D.
Associate Professor
Pennington Biomedical Research Center
Louisiana State University System
6400 Perkins Road
Baton Rouge, LA 70808

(225) 763-2782



-----Original Message-----
From: bioconductor-bounces@r-project.org on behalf of Steve Lianoglou
Sent: Sun 12/2/2012 4:41 AM
To: Gordon K Smyth
Cc: Bioconductor mailing list
Subject: Re: [BioC] gene set enrichment
 
Hi Gordon,

When an expert comments on a topic I'm interested in, it's hard for me
not to press for more insight so I hope you don't mind, but also ...
you know .. take your time :-)

On Sat, Dec 1, 2012 at 8:39 PM, Gordon K Smyth <smyth@wehi.edu.au> wrote:
[snip]
> The term "gene set enrichment analysis" was coined by the Broad Institute:
>
>   http://www.broadinstitute.org/gsea/
>
> but you certainly can't simply give a list of genes to GSEA.  It requires
> complete data and is designed for microarrays rather than RNA-Seq anyway.

I'm curious if you say so because GSEA doesn't account for something
like length bias? The GSEA folks seem to suggest that one could do
this like any other "pre-processed" GSEA analysis by simply providing
a ranked list of genes (presumably by fold-change):

http://www.broadinstitute.org/cancer/software/gsea/wiki/index.php/FAQ#Can_I_use_GSEA_to_analyze_SNP.2C_SAGE.2C_ChIP-Seq_or_RNA-Seq_data.3F

Would you mind (briefly) elaborating a bit on why you disagree?

Thanks,
-steve

-- 
Steve Lianoglou
Graduate Student: Computational Systems Biology
 | Memorial Sloan-Kettering Cancer Center
 | Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact

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