# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "ashr" in publications use:' type: software title: 'ashr: Methods for Adaptive Shrinkage, using Empirical Bayes' version: 2.2-66 doi: 10.32614/CRAN.package.ashr abstract: '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. 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).' authors: - family-names: Stephens given-names: Matthew email: mstephens@uchicago.edu - family-names: Carbonetto given-names: Peter email: pcarbo@uchicago.edu - family-names: Gerard given-names: David - family-names: Lu given-names: Mengyin - family-names: Sun given-names: Lei - family-names: Willwerscheid given-names: Jason - family-names: Xiao given-names: Nan repository: https://stephens999.r-universe.dev repository-code: https://github.com/stephens999/ashr commit: 6786aa1511d31606ffa5f3e312d5698649049f73 url: https://github.com/stephens999/ashr date-released: '2024-05-14' contact: - family-names: Carbonetto given-names: Peter email: pcarbo@uchicago.edu