[BioC] New gage package: Generally Applicable Gene-set/Pathway Analysis

[Luo Weijun]

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 http://bioconductor.org/help/bioc-views/release/bioc/html/gage.html, if you are doing gene set analysis, general microarray or sequencing data analysis.

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