Package: milorGWAS 0.7

Hervé Perdry

milorGWAS: Mixed Logistic Regression for Genome-Wide Analysis Studies (GWAS)

Fast approximate methods for mixed logistic regression in genome-wide analysis studies (GWAS). Two computationnally efficient methods are proposed for obtaining effect size estimates (beta) in Mixed Logistic Regression in GWAS: the Approximate Maximum Likelihood Estimate (AMLE), and the Offset method. The wald test obtained with AMLE is identical to the score test. Data can be genotype matrices in plink format, or dosage (VCF files). The methods are described in details in Milet et al (2020) <doi:10.1101/2020.01.17.910109>.

Authors:Hervé Perdry [aut, cre], Jacqueline Milet [aut]

milorGWAS_0.7.tar.gz
milorGWAS_0.7.tar.gz(r-4.5-noble)milorGWAS_0.7.tar.gz(r-4.4-noble)
milorGWAS_0.7.tgz(r-4.4-emscripten)milorGWAS_0.7.tgz(r-4.3-emscripten)
milorGWAS.pdf |milorGWAS.html
milorGWAS/json (API)
NEWS

# Install 'milorGWAS' in R:
install.packages('milorGWAS', repos = 'https://cloud.r-project.org')
Uses libs:
  • zlib– Compression library
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

zlibcpp

2.00 score 481 downloads 1 mentions 4 exports 4 dependencies

Last updated 9 months agofrom:4e24b9342b. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 21 2025
R-4.5-linux-x86_64OKMar 21 2025
R-4.4-linux-x86_64OKMar 21 2025

Exports:association.test.logisticassociation.test.logistic.dosageqqplot.pvaluesSNP.category

Dependencies:gastonRcppRcppEigenRcppParallel

milorGWAS package

Rendered frommilorGWAS.Rmdusingknitr::rmarkdownon Mar 21 2025.

Last update: 2024-06-22
Started: 2020-03-25

Citation

To cite package ‘milorGWAS’ in publications use:

Perdry H, Milet J (2024). milorGWAS: Mixed Logistic Regression for Genome-Wide Analysis Studies (GWAS). R package version 0.7, https://CRAN.R-project.org/package=milorGWAS.

Corresponding BibTeX entry:

  @Manual{,
    title = {milorGWAS: Mixed Logistic Regression for Genome-Wide
      Analysis Studies (GWAS)},
    author = {Hervé Perdry and Jacqueline Milet},
    year = {2024},
    note = {R package version 0.7},
    url = {https://CRAN.R-project.org/package=milorGWAS},
  }