Non-Local Prior Based Iterative Variable Selection Tool for Genome-Wide Association Studies R package GWASinlps version 2.4 Performs variable selection with data from Genome-wide association studies (GWAS), or other high-dimensional data with continuous, binary or survival outcomes, combining in an iterative framework the computational efficiency of the structured screen-and-select variable selection strategy based on some association learning and the parsimonious uncertainty quantification provided by the use of non-local priors (see Sanyal et al., 2019 <DOI:10.1093/bioinformatics/bty472>). Software Depends: mombf Imports: Rcpp (>= 1.0.9), RcppArmadillo, fastglm, survival LinkingTo: Rcpp, RcppArmadillo Suggests: glmnet Nilotpal Sanyal <nilotpal.sanyal@gmail.com> Comprehensive R Archive Network (CRAN) Nilotpal Sanyal [aut, cre] (ORCID: <https://orcid.org/0000-0003-4814-7602>) GPL (>= 2) 2025-10-29 application/tgz https://CRAN.R-project.org/package=GWASinlps doi:10.32614/CRAN.package.GWASinlps