Multivariate Adaptive Shrinkage R package mashr version 0.2.79 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. Software 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 Peter Carbonetto <peter.carbonetto@gmail.com> Comprehensive R Archive Network (CRAN) 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] BSD_3_clause + file LICENSE (https://CRAN.R-project.org/package=mashr/LICENSE) 2023-10-18 application/tgz https://CRAN.R-project.org/package=mashr doi:10.32614/CRAN.package.mashr