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ashr

Methods for Adaptive Shrinkage, using Empirical Bayes

v2.2-63 · Aug 21, 2023 · GPL (>= 3)

Description

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. 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).

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14 OK
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r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Reverse Dependencies (11)

depends

Dependency Network

Dependencies Reverse dependencies Matrix Rcpp truncnorm mixsqp SQUAREM etrunct invgamma mashr MixTwice ebnm fastTopics ldsep limorhyde2 smashr colocboost flashier ncvreg palasso ashr

Version History

new 2.2-63 Mar 10, 2026
updated 2.2-63 ← 2.2-54 diff Aug 21, 2023
updated 2.2-54 ← 2.2-47 diff Feb 21, 2022
updated 2.2-47 ← 2.2-40 diff Feb 19, 2020
updated 2.2-40 ← 2.2-39 diff Feb 2, 2020
updated 2.2-39 ← 2.2-32 diff Oct 16, 2019
updated 2.2-32 ← 2.2-7 diff Feb 21, 2019
updated 2.2-7 ← 2.0.5 diff Feb 28, 2018
new 2.0.5 Dec 26, 2016