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milorGWAS (version 0.7.1)

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

Description

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) .

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Install

install.packages('milorGWAS')

Monthly Downloads

180

Version

0.7.1

License

GPL-3

Maintainer

Herv<c3><a9> Perdry

Last Published

August 26th, 2025

Functions in milorGWAS (0.7.1)

association.test.logistic.dosage

Mixed logistic regression for GWAS, using dosages
SNP.category

SNP.category
association.test.logistic

Mixed logistic regression for GWAS
qqplot.pvalues

Stratified QQ-plot of p-values