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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "mashr" in publications use:'
type: software
license: BSD-3-Clause
title: 'mashr: Multivariate Adaptive Shrinkage'
version: 0.2.79
identifiers:
- type: doi
  value: 10.32614/CRAN.package.mashr
abstract: 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.
authors:
- family-names: Stephens
  given-names: Matthew
- family-names: Urbut
  given-names: Sarah
- family-names: Wang
  given-names: Gao
- family-names: Zou
  given-names: Yuxin
- family-names: Carbonetto
  given-names: Peter
  email: peter.carbonetto@gmail.com
preferred-citation:
  type: article
  title: Flexible statistical methods for estimating and testing effects in genomic
    studies with multiple conditions
  authors:
  - name: Sarah Urbut
  - name: Gao Wang
  - name: Peter Carbonetto
  - name: Matthew Stephens
  journal: Nature Genetics
  volume: '51'
  issue: '1'
  year: '2019'
  start: '187'
  end: '195'
repository: https://stephenslab.r-universe.dev
repository-code: https://github.com/stephenslab/mashr
commit: cbf046294caeecb3f84d3c588c14bb29ca3f8f39
url: https://github.com/stephenslab/mashr
date-released: '2023-10-18'
contact:
- family-names: Carbonetto
  given-names: Peter
  email: peter.carbonetto@gmail.com