This package is an implementation the Quantitative Set Analysis for Gene Expression (QuSAGE) method described in (Yaari G. et al, Nucl Acids Res, 2013). This is a novel Gene Set Enrichmenttype test, which is designed to provide a faster, more accurate, and easier to understand test for gene expression studies. qusage accounts for intergene correlations using the Variance Inflation Factor technique 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 posthoc analysis (e.g., pairwise 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 Welchbased method is implemented that is shown to improve specificity. The QuSAGE package also includes a mixed effects model implementation, as described in (Turner JA et al, BMC Bioinformatics, 2015), and a metaanalysis framework as described in (Meng H, et al. PLoS Comput Biol. 2019). For questions, contact Chris Bolen (cbolen1@gmail.com) or Steven Kleinstein (steven.kleinstein@yale.edu)
Package details 


Author  Christopher Bolen and Gur Yaari, with contributions from Juilee Thakar, Hailong Meng, Jacob Turner, Derek Blankenship, and Steven Kleinstein 
Bioconductor views  GeneSetEnrichment ImmunoOncology Microarray RNASeq Software 
Maintainer  Christopher Bolen <cbolen1@gmail.com> 
License  GPL (>= 2) 
Version  2.22.0 
URL  http://clip.med.yale.edu/qusage 
Package repository  View on Bioconductor 
Installation 
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