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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
