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mvMAPIT

2.0.4Package record

Multivariate Genome Wide Marginal Epistasis Test

1packages depend
4.4Kdownloads / year
97.2%test coverage
13/13flavors OK

Overview

About

Epistasis, commonly defined as the interaction between genetic loci, is known to play an important role in the phenotypic variation of complex traits. As a result, many statistical methods have been developed to identify genetic variants that are involved in epistasis, and nearly all of these approaches carry out this task by focusing on analyzing one trait at a time. Previous studies have shown that jointly modeling multiple phenotypes can often dramatically increase statistical power for association mapping. In this package, we present the 'multivariate MArginal ePIstasis Test' ('mvMAPIT') – a multi-outcome generalization of a recently proposed epistatic detection method which seeks to detect marginal epistasis or the combined pairwise interaction effects between a given variant and all other variants. By searching for marginal epistatic effects, one can identify genetic variants that are involved in epistasis without the need to identify the exact partners with which the variants interact – thus, potentially alleviating much of the statistical and computational burden associated with conventional explicit search based methods. Our proposed 'mvMAPIT' builds upon this strategy by taking advantage of correlation structure between traits to improve the identification of variants involved in epistasis. We formulate 'mvMAPIT' as a multivariate linear mixed model and develop a multi-trait variance component estimation algorithm for efficient parameter inference and P-value computation. Together with reasonable model approximations, our proposed approach is scalable to moderately sized genome-wide association studies. Crawford et al. (2017) doi:10.1371/journal.pgen.1006869. Stamp et al. (2023) doi:10.1093/g3journal/jkad118. Stamp et al. (2025) doi:10.1016/j.ajhg.2025.07.004.

Changes in 2.0.4
  • Fix Bonferroni correction in the mvMAPIT.Rmd vignette.
  • New function binary_to_liability for LT-MAPIT support and corresponding vignette
  • Fix CRAN Notes - dependency compatibility.
  • Performance improvements in C++ implementation:
  • Eliminated redundant matrix inverse computation in projection operations
  • Optimized triple matrix products in Q matrix computation
  • Added benchmark suite for tracking performance improvements
  • Typical speedup: 3-8% depending on problem size and test method

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 7.7 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-09-09
  • ERROR12 OK, 1 ERROR2026-09-04
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
Show 7 earlier changesHide 7 earlier changes
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK12 OK2026-04-25
  • NOTE12 OK, 2 NOTE2026-04-22
  • ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
  • NOTE12 OK, 2 NOTE2026-04-10
  • ERROR11 OK, 2 NOTE, 1 ERROR2026-04-09
  • NOTE12 OK, 2 NOTE2026-03-10
Advisories

none known

Documentation

In release 2.0.4
READMEYes · 1,183 wordsVignettesYes · 7 · dynamicNEWSYes · 100% structured · mentions 2.0.4Citation fileNoWebsiteYes · pkgdown
Help pages
9
Examples that run
100%5 run in a plain check
Exported functions with examples
83%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
0%

Downloads

4.4K
CRAN downloads in the past year
Rank #13,072 · ~12/day · ~366/mo
Daily download trend is not available in this view yet.
36530 days
87390 days
4.4K1 year
Compare downloads with other packages →
Also on380 r2u4 autocran

Repository

14Stars
2Forks
3Open issues
0Open PRs
13Releases
125Commits
3Commit identities
epistasismapitmvmapitrvariance-componentscppcranepistasis-analysis
License file reads as GPL-3.0 · 125 commits · Last activity 2026-02-20 · 0% stars, 30d
Responsiveness
How these are sampled
PRs merged (all time)
92%
Median days to close, 50 most recently updated closed issues
154
Median days to close, 50 most recently updated closed PRs
0

Stars over time

2025-06-26 · 122026-07-07 · 14
PracticesBeta

8 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/lcrawlab/mvmapit on 2026-10-18.

Continuous integration (2)
GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows

Governance and community (1)
CODEOWNERS
Docs source (3)
pkgdown

GitHub Pages site last deployed 2026-02-20 · The repository has a site deploy workflow

pkgdown site last built 2026-02-20, before release 2.0.4 (2026-02-22)

Reproducibility and dev environment (2)
data-raw/Dockerfile
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
25 external dependencies (excludes base and recommended)

Installing mvMAPIT adds 52 packages (29 with compiled code, 29 MB of source tarballs). Heaviest: stringi 11 MB, Rcpp 1.8 MB, fs 1.4 MB.

Depends (1)
R >= 3.5
Enhances (0)
none
Reverse dependencies
1direct
0indirect
Imports 1
Depends, Imports or LinkingTo, most downloaded first

Datasets

People & History

People (2)
Maintainer since 2.0.0 (2022), Author
Releases (5)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 2.0.4Latest
    record
    2026-02-22 · current release · diff ↗ ·
    added 1 export
    binary_to_liability
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • 2.0.3
    record
    2023-09-26 · diff ↗
  • 2.0.2
    record
    2023-09-22 · diff ↗ ·
    added 1 export
    cauchy_combined
  • R
    R 4.3.0 released · 2023-04-21
  • unarchivedReturned to CRAN
    2023-02-09
  • 2.0.1
    record
    2023-02-09 · diff ↗
  • archivedRemoved from CRAN
    2023-01-10
    issues were not corrected in time
  • 2.0.0
    record
    2022-12-05
  • R
    R 4.2.0 released · 2022-04-22

Package metadata

First published
2022-12-05
Total releases
5 / 4 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 3.5
Bundled data
205 KB / 3 files
Download size
903 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("mvMAPIT")
Stamp, J., & Crawford, L. (2026). mvMAPIT: Multivariate Genome Wide Marginal Epistasis Test (Version 2.0.4) [Computer software]. https://doi.org/10.32614/CRAN.package.mvMAPIT

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for mvMAPIT version 2.0.4 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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