GCPBayes: Bayesian Meta-Analysis of Pleiotropic Effects Using Group Structure

Run a Gibbs sampler for a multivariate Bayesian sparse group selection model with Dirac, continuous and hierarchical spike prior for detecting pleiotropy on the traits. This package is designed for summary statistics containing estimated regression coefficients and its estimated covariance matrix. The methodology is available from: Baghfalaki, T., Sugier, P. E., Truong, T., Pettitt, A. N., Mengersen, K., & Liquet, B. (2021) <doi:10.1002/sim.8855>.

Version: 4.0.0
Depends: R (≥ 3.5.0)
Imports: MASS, mvtnorm, invgamma, gdata, truncnorm, postpack, wiqid
Published: 2022-11-02
Author: Taban Baghfalaki
Maintainer: Taban Baghfalaki <t.baghfalaki at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
NeedsCompilation: no
Materials: NEWS
CRAN checks: GCPBayes results


Reference manual: GCPBayes.pdf


Package source: GCPBayes_4.0.0.tar.gz
Windows binaries: r-devel: GCPBayes_4.0.0.zip, r-release: GCPBayes_4.0.0.zip, r-oldrel: GCPBayes_4.0.0.zip
macOS binaries: r-release (arm64): GCPBayes_4.0.0.tgz, r-oldrel (arm64): GCPBayes_4.0.0.tgz, r-release (x86_64): GCPBayes_4.0.0.tgz, r-oldrel (x86_64): GCPBayes_4.0.0.tgz
Old sources: GCPBayes archive


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