An R package for quantitative analysis of gene expression data


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.


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


Additional information is available at:


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