QuSAGE

An R package for quantitative analysis of gene expression data

Introduction:

This package is an implementation the Quantitative Set Analysis for Gene Expression (QuSAGE) method described in Yaari et al. (Nucleic Acids Res, 2013). This is a novel Gene Set Enrichment-type test, which is designed to provide a faster, more accurate, and easier to understand test for gene expression studies. QuSAGE accounts for inter-gene correlations using a Variance Inflation Factor technique that extends the method proposed by Wu et al. (Nucleic Acids Res, 2012). In addition, rather than simply evaluating the deviation from a null hypothesis with a single number (a P value), QuSAGE quantifies gene set activity with a complete probability density function (PDF). From this PDF, P values and confidence intervals can be easily extracted. Preserving the PDF also allows for post-hoc analysis (e.g., pair-wise comparisons of gene set activity) while maintaining statistical traceability. Finally, while QuSAGE is compatible with individual gene statistics from existing methods (e.g., LIMMA), a Welch-based method is implemented that is shown to improve specificity.

Installation:

The QuSAGE package is available through Bioconductor using the biocLite command.
To install the package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("qusage")

Additional information is available at:

http://bioconductor.org/packages/release/bioc/html/qusage.html

Instructions for use:

Instructions for using the QuSAGE package are detailed in a short vignette, which is available at the bioconductor website, listed above.

Citing QuSAGE:

When including the results of the QuSAGE package in a publication, please cite the following paper:

Yaari G, Bolen CR, Thakar J, Kleinstein SH. Quantitative set analysis for gene expression: a method to quantify gene set differential expression including gene-gene correlations. Nucleic Acids Res. 2013 Aug 5. PubMed PMID: 23921631

For questions, comments, or requests, please contact Steven Kleinstein at steven.kleinstein@yale.edu