Package: milorGWAS
Type: Package
Title: Mixed Logistic Regression for Genome-Wide Analysis Studies
        (GWAS)
Version: 0.7.1
Date: 2025-08-26
Encoding: UTF-8
Authors@R: c(person("Hervé", "Perdry", role = c("cre", "aut"), email = "herve.perdry@universite-paris-saclay.fr"), 
             person("Jacqueline", "Milet", role = "aut") )
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) <doi:10.1101/2020.01.17.910109>.
License: GPL-3
Imports: Rcpp (>= 1.0.2)
Depends: gaston (>= 1.6)
LinkingTo: Rcpp, RcppEigen, gaston
Suggests: knitr, rmarkdown, png
VignetteBuilder: knitr
NeedsCompilation: yes
RoxygenNote: 7.3.2
Packaged: 2025-08-26 15:02:21 UTC; rv
Author: Hervé Perdry [cre, aut],
  Jacqueline Milet [aut]
Maintainer: Hervé Perdry <herve.perdry@universite-paris-saclay.fr>
Repository: CRAN
Date/Publication: 2025-08-26 16:30:02 UTC
Built: R 4.5.1; x86_64-apple-darwin20; 2025-08-26 17:43:33 UTC; unix
Archs: milorGWAS.so.dSYM
