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