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", <doi:10.1093/biostatistics/kxw041>. 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.
|Depends:||R (≥ 3.1.0)|
|Imports:||assertthat, truncnorm, SQUAREM, doParallel, pscl, Rcpp (≥ 0.10.5), foreach, etrunct|
|Suggests:||testthat, roxygen2, covr|
|Author:||Matthew Stephens, Chaoxing Dai, Mengyin Lu, David Gerard, Nan Xiao, Peter Carbonetto|
|Maintainer:||Peter Carbonetto <pcarbo at uchicago.edu>|
|License:||GPL (≥ 3)|
|CRAN checks:||ashr results|
|Windows binaries:||r-devel: ashr_2.0.5.zip, r-release: ashr_2.0.5.zip, r-oldrel: ashr_2.0.5.zip|
|OS X Mavericks binaries:||r-release: ashr_2.0.5.tgz, r-oldrel: ashr_2.0.5.tgz|
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