[BioC] New gage package: Generally Applicable Gene-set/Pathway Analysis
edwin.groot at biologie.uni-freiburg.de
Wed Oct 20 12:12:27 CEST 2010
On Tue, 19 Oct 2010 10:54:16 -0700 (PDT)
Luo Weijun <luo_weijun at yahoo.com> wrote:
> Dear Bioconductor users,
> I’d like to introduce my gage package newly released with Bioc 2.7.
> Although the first version of gage package came out about two years
> ago, this is its first release with Bioc. Please take a look at gage
> package at
> if you are doing gene set analysis, general microarray or sequencing
> data analysis.
Nice to see it in Bioconductor now. Good show, Weijun!
> Gene set analysis (GSA, also called or pathway analysis) is a
> powerful strategy to infer functional and mechanistic changesfrom
> high through microarray data. However, classical GSA methodsonly have
> limited usage to a small number of microarray studies as they cannot
> handle datasets of different sample sizes, experimental designs,
> microarray platforms, and other types of heterogeneity. To address
> these limitations, we developed and published a new method called
> Generally Applicable Gene-set Enrichment (GAGE). Besides general
> applicability, we’ve also showed that GAGE consistently achieves
> superior or similar performance over other frequently used methods.
> In gage package, we provide functions for basic GAGE analysis, result
> processing and presentation. We have also built pipeline routines for
> of multiple GAGE analyses in a batch, comparison between parallel
> analyses, and combined analysis of heterogeneous data from different
> sources/studies. In addition, we provide demo microarray data and
> commonly used gene set data based on KEGG pathways and GO terms.
> These funtions and data are also useful for gene set analysis using
> other methods.
> We also release a supportive data package, gageData, which includes
> two full microarray datasets and gene set data based on KEGG pathways
> and GO terms for major research species, including human, mouse, rat
> and budding yeast.
> Please let me know if you have any questions/comments/suggestions.
> Thank you for your interest!
> Weijun Luo
Because I had to analyze experiments with 3 or 4 replicates, GAGE was
the GSA package of choice. GSEA requires about 8 replicates per
Dr. Edwin Groot, postdoctoral associate
Institut fuer Biologie III
79104 Freiburg, Deutschland
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