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) .


Reference manual

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install.packages("milorGWAS")

0.7.1 by Hervé Perdry, a year ago


Browse source code at https://github.com/cran/milorGWAS


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


Documentation:   PDF Manual  


GPL-3 license


Imports Rcpp

Depends on gaston

Suggests knitr, rmarkdown, png

Linking to Rcpp, RcppEigen, gaston


See at CRAN