Package: plmmr 4.2.1

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/>.

Authors:Tabitha K. Peter [aut], Anna C. Reisetter [aut], Patrick J. Breheny [aut, cre], Yujing Lu [aut]

plmmr_4.2.1.tar.gz
plmmr_4.2.1.zip(r-4.5)plmmr_4.2.1.zip(r-4.4)
plmmr_4.2.1.tgz(r-4.5-x86_64)plmmr_4.2.1.tgz(r-4.5-arm64)plmmr_4.2.1.tgz(r-4.4-x86_64)plmmr_4.2.1.tgz(r-4.4-arm64)
plmmr_4.2.1.tar.gz(r-4.5-noble)plmmr_4.2.1.tar.gz(r-4.4-noble)
plmmr_4.2.1.tgz(r-4.4-emscripten)
plmmr.pdf |plmmr.html✨
plmmr/json (API)
NEWS

# Install 'plmmr' in R:
install.packages('plmmr', repos = c('https://pbreheny.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pbreheny/plmmr/issues

Pkgdown site:https://pbreheny.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • admix - Admix: Semi-simulated SNP data

On CRAN:

Conda-Forge:

cppopenmp

6.31 score 4 stars 10 scripts 393 downloads 9 exports 19 dependencies

Last updated 2 hours agofrom:d65dd57177. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 05 2025
R-4.5-win-x86_64OKMar 05 2025
R-4.5-mac-x86_64OKMar 05 2025
R-4.5-mac-aarch64OKMar 05 2025
R-4.5-linux-x86_64OKMar 05 2025
R-4.4-win-x86_64OKMar 05 2025
R-4.4-mac-x86_64OKMar 05 2025
R-4.4-mac-aarch64OKMar 05 2025
R-4.4-linux-x86_64OKMar 05 2025

Exports:create_designcv_plmmfind_example_dataplmmplmm_lossprocess_delimprocess_plinkrelatedness_matunzip_example_data

Dependencies:BHbigalgebrabiglassobigmemorybigmemory.sricodetoolsdata.tableforeachglmnetiteratorslatticeMatrixncvregRcppRcppArmadilloRcppEigenshapesurvivaluuid

Getting started with plmmr

Tabitha Peter

Rendered fromgetting-started.Rmdusingknitr::rmarkdownon Mar 05 2025.

Last update: 2024-10-22
Started: 2023-04-06