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GWASinlps: Non-Local Prior Based Iterative Variable Selection Tool forGenome-Wide Association Studies

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>).

Version:2.4
Depends:mombf
Imports:Rcpp (≥ 1.0.9),RcppArmadillo,fastglm,survival
LinkingTo:Rcpp,RcppArmadillo
Suggests:glmnet
Published:2025-10-29
DOI:10.32614/CRAN.package.GWASinlps
Author:Nilotpal SanyalORCID iD [aut, cre]
Maintainer:Nilotpal Sanyal <nilotpal.sanyal at gmail.com>
BugReports:https://github.com/nilotpalsanyal/GWASinlps/issues
License:GPL-2 |GPL-3 [expanded from: GPL (≥ 2)]
URL:https://nilotpalsanyal.github.io/GWASinlps/
NeedsCompilation:yes
Materials:README,NEWS
CRAN checks:GWASinlps results

Documentation:

Reference manual:GWASinlps.html ,GWASinlps.pdf

Downloads:

Package source: GWASinlps_2.4.tar.gz
Windows binaries: r-devel:GWASinlps_2.4.zip, r-release:GWASinlps_2.4.zip, r-oldrel:GWASinlps_2.4.zip
macOS binaries: r-release (arm64):GWASinlps_2.4.tgz, r-oldrel (arm64):GWASinlps_2.4.tgz, r-release (x86_64):GWASinlps_2.4.tgz, r-oldrel (x86_64):GWASinlps_2.4.tgz
Old sources: GWASinlps archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=GWASinlpsto link to this page.


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