The R package 'ashr' implements an Empirical Bayes approach for largescale 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 statisticsestimated effects and standard errorsare available, just as 'qvalue' can be applied to previously computed pvalues. Two main interfaces are provided: ash(), which is more userfriendly; and ash.workhorse(), which has more options and is geared toward advanced users. The ash() and ash.workhorse() also provides a flexible modeling interface that can accommodate a variety of likelihoods (e.g., normal, Poisson) and mixture priors (e.g., uniform, normal).
Package details 


Maintainer  Peter Carbonetto <[email protected]> 
License  GPL (>=3) 
Version  2.247 
URL  https://github.com/stephens999/ashr 
Package repository  View on GitHub 
Installation 
Install the latest version of this package by entering the following in R:

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