ashr (2.0.5)

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Methods for Adaptive Shrinkage, using Empirical Bayes.

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.

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

License: GPL (>= 3)

Uses: assertthat, doParallel, etrunct, foreach, pscl, Rcpp, SQUAREM, truncnorm, testthat, roxygen2, covr
Enhances: rmosek, REBayes

Released about 1 year ago.



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