Implements the multivariate adaptive shrinkage (mash) method of Urbut et al (2019) <doi:10.1038/s41588-018-0268-8> for estimating and testing large numbers of effects in many conditions (or many outcomes). Mash takes an empirical Bayes approach to testing and effect estimation; it estimates patterns of similarity among conditions, then exploits these patterns to improve accuracy of the effect estimates. The core linear algebra is implemented in C++ for fast model fitting and posterior computation.
Version: 0.2.79 Depends: R (≥ 3.3.0), ashr (≥ 2.2-22) Imports: assertthat, utils, stats, plyr, rmeta, Rcpp (≥ 1.0.8), mvtnorm, abind, softImpute LinkingTo: Rcpp, RcppArmadillo, RcppGSL (≥ 0.3.8) Suggests: MASS, REBayes, corrplot (≥ 0.90), testthat, kableExtra, knitr, rmarkdown, profmem, flashier, ebnm Published: 2023-10-18 DOI: 10.32614/CRAN.package.mashr Author: Matthew Stephens [aut], Sarah Urbut [aut], Gao Wang [aut], Yuxin Zou [aut], Yunqi Yang [ctb], Sam Roweis [cph], David Hogg [cph], Jo Bovy [cph], Peter Carbonetto [aut, cre] Maintainer: Peter Carbonetto <peter.carbonetto at gmail.com> BugReports: https://github.com/stephenslab/mashr/issues License: BSD_3_clause + file LICENSE Copyright: file COPYRIGHTSPlease use the canonical form https://CRAN.R-project.org/package=mashr to link to this page.
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