Another useful package is "piano": http://www.bioconductor.org/packages/release/bioc/html/piano.html Guido -----Original Message----- From: bioconductor-bounces@r-project.org [mailto:bioconductor- bounces@r-project.org] On Behalf Of Steve Lianoglou Sent: Monday, March 31, 2014 21:23 To: Enrico Ferrero Cc: bioconductor at r-project.org Subject: Re: [BioC] Running the GSEA algorithm Hi, For more GSEA options, check out the camera, roast, and romer function in limma (2/3 of those are also in edgeR). The respective vignettes have more info. -steve On Mon, Mar 31, 2014 at 12:19 PM, Enrico Ferrero <enricoferrero86 at="" gmail.com=""> wrote: > Hi everyone, > > I would like to include GSEA into my R analytical pipelines, but I'm > struggling to understand what's the best way to implement it. The > following information might be incomplete or even wrong, but here is > what I understood so far: > > - The GSEABase package [1] provides an excellent infrastructure for > dealing with gene sets and gene sets collections but, as far as I > understand, doesn't provide a way to run the GSEA algorithm. > > - The PGSEA package [2] provides a minimal, and perhaps simplistic, > interface to GSEA. It does run the analysis but only outputs a matrix > with what I understand is a score (possibly the NES?) and nothing else. > > - The SeqGSEA package [3] allows to run the GSEA algorithm and also > produces some excellent plots of gene sets enrichment. However, it > works with with RNA-seq count data and I don't see how it could be > adapted to microarray data. > > - The GSEA-P-R package from the Broad Institute [4] is arguably not > ideal to work with and its use is basically discouraged. > > - The Java version of GSEA [4] is probably my best bet at the moment, > as it allows command-line usage and provides a complete output for the analysis. > > So, am I missing something here? > Is there an established way to run the GSEA algorithm from R using > Bioconductor packages that also works for non-NGS data? > If not, would anybody recommend the GSEA-P-R package from the Broad > Institute? > Are there any other options? > > Thanks very much. > Best, > > [1] > http://www.bioconductor.org/packages/release/bioc/html/GSEABase.html > [2] http://www.bioconductor.org/packages/release/bioc/html/PGSEA.html > [3] > http://www.bioconductor.org/packages/release/bioc/html/SeqGSEA.html > [4] http://www.broadinstitute.org/gsea/downloads.jsp > > -- > Enrico Ferrero > Department of Genetics > Cambridge Systems Biology Centre > University of Cambridge > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor -- Steve Lianoglou Computational Biologist Genentech _______________________________________________ Bioconductor mailing list Bioconductor at r-project.org https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor

Hi, It's great to see all of these other packages popping out of the wood work. Bioc folks: Makes me wonder if we should add a GSEA biocView to help identify these more quickly ... I think it'd be handy. -steve On Mon, Mar 31, 2014 at 1:00 PM, Julian Gehring <julian.gehring at="" embl.de=""> wrote: > Hi Enrico, > > You can also have a look at the GSRI package: > http://bioconductor.org/packages/release/bioc/html/GSRI.html > > Best wishes > Julian > > > On 31/03/14 21:19, Enrico Ferrero wrote: >> Hi everyone, >> >> I would like to include GSEA into my R analytical pipelines, but I'm >> struggling to understand what's the best way to implement it. The following >> information might be incomplete or even wrong, but here is what I >> understood so far: >> >> - The GSEABase package [1] provides an excellent infrastructure for dealing >> with gene sets and gene sets collections but, as far as I understand, >> doesn't provide a way to run the GSEA algorithm. >> >> - The PGSEA package [2] provides a minimal, and perhaps simplistic, >> interface to GSEA. It does run the analysis but only outputs a matrix with >> what I understand is a score (possibly the NES?) and nothing else. >> >> - The SeqGSEA package [3] allows to run the GSEA algorithm and also >> produces some excellent plots of gene sets enrichment. However, it works >> with with RNA-seq count data and I don't see how it could be adapted to >> microarray data. >> >> - The GSEA-P-R package from the Broad Institute [4] is arguably not ideal >> to work with and its use is basically discouraged. >> >> - The Java version of GSEA [4] is probably my best bet at the moment, as it >> allows command-line usage and provides a complete output for the analysis. >> >> So, am I missing something here? >> Is there an established way to run the GSEA algorithm from R using >> Bioconductor packages that also works for non-NGS data? >> If not, would anybody recommend the GSEA-P-R package from the Broad >> Institute? >> Are there any other options? >> >> Thanks very much. >> Best, >> >> [1] http://www.bioconductor.org/packages/release/bioc/html/GSEABase.html >> [2] http://www.bioconductor.org/packages/release/bioc/html/PGSEA.html >> [3] http://www.bioconductor.org/packages/release/bioc/html/SeqGSEA.html >> [4] http://www.broadinstitute.org/gsea/downloads.jsp >> > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- Steve Lianoglou Computational Biologist Genentech