plmmr: Penalized Linear Mixed Models for Correlated Data

Fits penalized linear mixed models that correct for unobserved confounding factors. 'plmmr' infers and corrects for the presence of unobserved confounding effects such as population stratification and environmental heterogeneity. It then fits a linear model via penalized maximum likelihood. Originally designed for the multivariate analysis of single nucleotide polymorphisms (SNPs) measured in a genome-wide association study (GWAS), 'plmmr' eliminates the need for subpopulation-specific analyses and post-analysis p-value adjustments. Functions for the appropriate processing of 'PLINK' files are also supplied. For examples, see the package homepage. <https://pbreheny.github.io/plmmr/>.

Version: 4.1.0
Depends: bigalgebra, bigmemory, R (≥ 4.4.0)
Imports: biglasso (≥ 1.6.0), data.table, glmnet, Matrix, ncvreg, parallel, utils
LinkingTo: BH, bigmemory, Rcpp, RcppArmadillo (≥ 0.8.600)
Suggests: bigsnpr, bigstatsr, graphics, grDevices, knitr, MASS, rmarkdown, tinytest
Published: 2024-10-23
DOI: 10.32614/CRAN.package.plmmr
Author: Tabitha K. Peter ORCID iD [aut], Anna C. Reisetter ORCID iD [aut], Patrick J. Breheny ORCID iD [aut, cre], Yujing Lu [aut]
Maintainer: Patrick J. Breheny <patrick-breheny at uiowa.edu>
License: GPL-3
URL: https://pbreheny.github.io/plmmr/, https://github.com/pbreheny/plmmr/
NeedsCompilation: yes
Citation: plmmr citation info
Materials: README NEWS
CRAN checks: plmmr results

Documentation:

Reference manual: plmmr.pdf
Vignettes: Getting started with plmmr (source, R code)

Downloads:

Package source: plmmr_4.1.0.tar.gz
Windows binaries: r-devel: plmmr_4.1.0.zip, r-release: plmmr_4.1.0.zip, r-oldrel: not available
macOS binaries: r-release (arm64): plmmr_4.1.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): plmmr_4.1.0.tgz, r-oldrel (x86_64): not available
Old sources: plmmr archive

Linking:

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