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Package: qusage
Version: 2.4.0
Date: 2013-01-20
Title: qusage: Quantitative Set Analysis for Gene Expression
Authors@R: c(person("Christopher Bolen", "Developer", role = c("aut",
"cre"), email = "cbolen1@gmail.com"), person("Gur Yaari",
"Developer", role = "aut"), person("Juilee Thakar",
"Developer", role = "aut"), person("Hailong Meng",
"Developer", role = "aut"), person("Jacob Turner",
"Developer", role = "aut"), person("Derek Blankenship",
"Developer", role = "aut"), person("Steven Kleinstein",
"Developer", role = "aut"))
Author: Christopher Bolen and Gur Yaari, with contributions from Juilee
Thakar, Hailong Meng, Jacob Turner, Derek Blankenship, and
Steven Kleinstein
Maintainer: Christopher Bolen <cbolen1@gmail.com>
Depends: R (>= 2.10), limma (>= 3.14), methods
Imports: utils, Biobase, nlme, lsmeans
Description: 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 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 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 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. For questions, contact Chris Bolen
(cbolen1@gmail.com) or Steven Kleinstein
(steven.kleinstein@yale.edu)
License: GPL (>= 2)
URL: http://clip.med.yale.edu/qusage
biocViews: GeneSetEnrichment, Microarray, RNASeq, Software
NeedsCompilation: no
Packaged: 2016-05-04 05:11:50 UTC; biocbuild
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providing 
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