NGBVS: Bayesian Variable Selection for SNP Data using Normal-Gamma

Posterior distribution of case-control fine-mapping. Specifically, Bayesian variable selection for single-nucleotide polymorphism (SNP) data using the normal-gamma prior. Alenazi A.A., Cox A., Juarez M,. Lin W-Y. and Walters, K. (2019) Bayesian variable selection using partially observed categorical prior information in fine-mapping association studies, Genetic Epidemiology. <doi:10.1002/gepi.22213>.

Version: 0.3.0
Depends: R (≥ 3.6.0)
Imports: stats, Rfast
Published: 2022-09-16
Author: Abdulaziz Alenazi [aut, cre]
Maintainer: Abdulaziz Alenazi <a.alenazi at nbu.edu.sa>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: NGBVS results

Documentation:

Reference manual: NGBVS.pdf

Downloads:

Package source: NGBVS_0.3.0.tar.gz
Windows binaries: r-prerel: NGBVS_0.3.0.zip, r-release: NGBVS_0.3.0.zip, r-oldrel: NGBVS_0.3.0.zip
macOS binaries: r-prerel (arm64): NGBVS_0.3.0.tgz, r-release (arm64): NGBVS_0.3.0.tgz, r-oldrel (arm64): NGBVS_0.3.0.tgz, r-prerel (x86_64): NGBVS_0.3.0.tgz, r-release (x86_64): NGBVS_0.3.0.tgz
Old sources: NGBVS archive

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