mashr: Multivariate Adaptive Shrinkage

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: 0.2.38
Depends: R (≥ 3.3.0), ashr (≥ 2.2-22)
Imports: assertthat, utils, stats, plyr, rmeta, Rcpp (≥ 0.12.11), mvtnorm, abind
LinkingTo: Rcpp, RcppArmadillo, RcppGSL
Suggests: MASS, REBayes, corrplot, testthat, kableExtra, knitr, rmarkdown, profmem
Published: 2020-06-19
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>
License: BSD_3_clause + file LICENSE
Copyright: file COPYRIGHTS
mashr copyright details
NeedsCompilation: yes
SystemRequirements: C++11
Citation: mashr citation info
Materials: README
CRAN checks: mashr results


Reference manual: mashr.pdf
Vignettes: using mashr for eQTL studies
mashr intro with correlations
mashr intro with data-driven covariances
mashr intro
mashcommonbaseline intro
mashnocommonbaseline intro
Sample from mash posteriors
mashr simulation with non-canonical matrices
Package source: mashr_0.2.38.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: mashr_0.2.38.tgz, r-oldrel: mashr_0.2.38.tgz
Old sources: mashr archive


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