[BioC] GSEA with one class metaanalysis

[Gordon Smyth]

Dear Mark,

If I understand your problem correctly, neither GSEA nor GSA will 
accomodate it. The only option I know of is geneSetTest() in the 
limma package. This generally works well, although it will give you 
someone over optimistic p-values if there are strong positive 
correlations between the genes in your gene sets.

Best wishes
Gordon

>Date: Fri, 02 Mar 2007 12:04:09 -0500
>From: Mark W Kimpel <mwkimpel at gmail.com>
>Subject: [BioC] GSEA with one class metaanalysis
>To: Bioconductor Newsgroup <bioconductor at stat.math.ethz.ch>
>
>I am in the process of performing a meta-analysis on multiple MA studies
>run on several platforms and several species. Although I realize there
>are probably other ways to approach the data, my collaborators have
>chosen to use Cohen's D-statistic to summarize their data.
>
>I would like to use GSEA to look for over-represented groups or pathways
>in the data, but what I will end up with is essentially a one-class
>experiment. In other words, I would like to identify groups whose
>summary D-statistic (I recognize from the recent literature that there
>is more than one summary method available) is different from zero.
>
>  From what I have read, the GSEA method is usually used to evaluate 2
>class data, the GSA method of Tibshurani can be used to evaluate
>multi-class data, but can either method be easily adapted to evaluate
>one class data? It would seem theoretically reasonable, but I don't know
>if I would have to modify one of the packages or if one already provides
>for this.
>
>And, while I'm at it, I will also want to look for individual genes
>whose average D-statistic is different from zero. I am advocating using
>a t-test with n=number of experiments with corresponding degrees of
>freedom, whereas others are advocating using a z-test because the
>D-statistics are summarizing many underlying individual statistics.
>
>Help with these questions would be deeply appreciated.
>
>Mark
>
>--
>Mark W. Kimpel MD
>Neuroinformatics
>Department of Psychiatry
>Indiana University School of Medicine