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mashr

An R package for multivariate adaptive shrinkage.

https://github.com/stephenslab/mashr

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    3 of 10 committers (30.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (18.5%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

An R package for multivariate adaptive shrinkage.

Basic Info
Statistics
  • Stars: 92
  • Watchers: 13
  • Forks: 21
  • Open Issues: 59
  • Releases: 11
Created about 9 years ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

mashr: Multivariate Adaptive Shrinkage in R

CRAN\_Status\_Badge Travis Build Status codecov

This package implements methods to estimate and test many effects in many conditions (or many effects on many outcomes).

Empirical Bayes methods are used to estimate patterns of similarity among conditions, then exploit these patterns of similarity among conditions to improve accuracy of effect estimates. See Urbut et al for details.

Note: the R package used to generate the results for the manuscript is here.

Quick Start

  1. Install mashr from CRAN: install.packages("mashr"). For more detailed setup instructions, see below.

  2. See the introductory vignette for an introduction to mashr.

  3. Then walk through these vignettes to learn more about mashr: Introduction to mash: data-driven covariances and Simulation with non-canonical matrices.

Citing this work

If you find the mashr package or any of the source code in this repository useful for your work, please cite:

Sarah Urbut, Gao Wang, Peter Carbonetto and Matthew Stephens (2019). Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions. Nature Genetics 51, 187-195.

Setup

The simplest and quickest to obtain mashr is to install it from CRAN:

R install.packages("mashr")

For Mac and Windows, usually the package is precompiled, so no additional compiler setup is required. If you have Linux, and in some other rare cases, you will need to make sure that your R installation is properly set up to compile packages with C++ source; in particular, the C++ compiler programs supported by your version of R should be installed on your computer, and R should be correctly configured to call these compilers when installing packages from source. For more information, see the CRAN documentation.

Alternatively, you may use remotes to install the latest version of mashr from GitHub:

R install.packages("remotes") remotes::install_github("stephenslab/mashr")

This command should automatically install any missing dependencies that are available from CRAN and GitHub.

Developer notes

  • When any changes are made to roxygen2 markup or the C++ code in the src directory, run devtools::document() to update the RcppExports.cpp, the package namespaces (see NAMESPACE), and the package documentation files (in the "man" subdirectory),

  • These are the R commands to build the website (make sure you are connected to Internet while running these commands):

R pkgdown::build_site(lazy=TRUE, examples=FALSE)

  • After editing C++ code in the src directory, please use uncrustify to format the code using configuration file inst/misc/uncrustify_default.cfg. For example:

bash uncrustify -c uncrustify_default.cfg --replace --no-backup -l CPP mash.cpp

  • Prior to submitting the package to CRAN, the following modifications need to be made: (1) remove the Remotes: entry in DESCRIPTION; and (2) remove the flash_mash.Rmd vignette.

Owner

  • Name: Stephens lab
  • Login: stephenslab
  • Kind: organization

Research in statistical and computational methods for genetics at the University of Chicago.

GitHub Events

Total
  • Issues event: 5
  • Watch event: 5
  • Issue comment event: 6
  • Push event: 5
  • Pull request event: 2
  • Fork event: 1
  • Create event: 1
Last Year
  • Issues event: 5
  • Watch event: 5
  • Issue comment event: 6
  • Push event: 5
  • Pull request event: 2
  • Fork event: 1
  • Create event: 1

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 829
  • Total Committers: 10
  • Avg Commits per committer: 82.9
  • Development Distribution Score (DDS): 0.619
Past Year
  • Commits: 33
  • Committers: 4
  • Avg Commits per committer: 8.25
  • Development Distribution Score (DDS): 0.182
Top Committers
Name Email Commits
Peter Carbonetto p****o@g****m 316
zouyuxin y****t@g****m 145
stephens999 s****9@g****m 135
Gao Wang g****w@u****u 135
Gao Wang w****w@g****m 88
Jason Willwerscheid w****d@u****u 4
Eric e****5@g****m 3
John Thiltges j****2@u****u 1
ajaynadig a****g@g****m 1
jmp448 j****7@g****m 1
Committer Domains (Top 20 + Academic)
uchicago.edu: 2 unl.edu: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 97
  • Total pull requests: 26
  • Average time to close issues: 5 months
  • Average time to close pull requests: 5 days
  • Total issue authors: 49
  • Total pull request authors: 9
  • Average comments per issue: 3.72
  • Average comments per pull request: 1.46
  • Merged pull requests: 20
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 13
  • Pull requests: 1
  • Average time to close issues: 7 days
  • Average time to close pull requests: about 19 hours
  • Issue authors: 11
  • Pull request authors: 1
  • Average comments per issue: 2.62
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • gaow (15)
  • stephens999 (11)
  • pcarbo (11)
  • arkyl (4)
  • lukeholman (4)
  • DongyueXie (2)
  • yrjia1015 (2)
  • resztak (2)
  • arider2 (2)
  • AlexSimis (2)
  • crvcheet21 (2)
  • willwerscheid (2)
  • Young-Sook (2)
  • william-denault (1)
  • Gongmian784 (1)
Pull Request Authors
  • zouyuxin (10)
  • gaow (8)
  • pcarbo (3)
  • surbut (1)
  • willwerscheid (1)
  • eweine (1)
  • ajaynadig (1)
  • jmp448 (1)
  • jthiltges (1)
Top Labels
Issue Labels
later (4) enhancement (3) bug (2) wontfix (1)
Pull Request Labels
enhancement (2)

Packages

  • Total packages: 1
  • Total downloads:
    • cran 445 last-month
  • Total docker downloads: 8
  • Total dependent packages: 1
  • Total dependent repositories: 2
  • Total versions: 6
  • Total maintainers: 1
cran.r-project.org: mashr

Multivariate Adaptive Shrinkage

  • Versions: 6
  • Dependent Packages: 1
  • Dependent Repositories: 2
  • Downloads: 445 Last month
  • Docker Downloads: 8
Rankings
Forks count: 3.9%
Stargazers count: 4.6%
Average: 15.1%
Dependent packages count: 18.2%
Downloads: 18.9%
Dependent repos count: 19.2%
Docker downloads count: 25.7%
Maintainers (1)
peter.carbonetto@gmail.com
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.3.0 depends
  • ashr >= 2.2 depends
  • Rcpp >= 0.12.11 imports
  • abind * imports
  • assertthat * imports
  • mvtnorm * imports
  • plyr * imports
  • rmeta * imports
  • softImpute * imports
  • stats * imports
  • utils * imports
  • MASS * suggests
  • REBayes * suggests
  • corrplot >= 0.90 suggests
  • flashr >= 0.6.7 suggests
  • kableExtra * suggests
  • knitr * suggests
  • profmem * suggests
  • rmarkdown * suggests
  • testthat * suggests