The R package 'ashr' implements an Empirical Bayes approach for large-scale hypothesis testing and false discovery rate (FDR) estimation based on the methods proposed in M. Stephens, 2016, "False discovery rates: a new deal", . These methods can be applied whenever two sets of summary statistics---estimated effects and standard errors---are available, just as 'qvalue' can be applied to previously computed p-values. Two main interfaces are provided: ash(), which is more user-friendly; and ash.workhorse(), which has more options and is geared toward advanced users.

Documentation

Manual: ashr.pdf
Vignette: None available.

Maintainer: Peter Carbonetto <pcarbo at uchicago.edu>

Author(s): Matthew Stephens, Chaoxing Dai, Mengyin Lu, David Gerard, Nan Xiao, Peter Carbonetto

Install package and any missing dependencies by running this line in your R console:

install.packages("ashr")

Depends R (>= 3.1.0)
Imports assertthat, truncnorm, SQUAREM, doParallel, pscl, Rcpp(>=0.10.5), foreach, etrunct
Suggests testthat, roxygen2, covr
Enhances REBayes, Rmosek
Linking to Rcpp
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Package ashr
Materials
URL http://github.com/stephens999/ashr
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Version 2.0.5
Published 2016-12-27
License GPL (>= 3)
BugReports
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks ashr check results
Package source ashr_2.0.5.tar.gz