Package: GCPBayes 4.2.0

Yazdan Asgari

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>.

Authors:Yazdan Asgari [aut, cre], Taban Baghfalaki [aut], Benoit Liquet [aut], Pierre-Emmanuel Sugier [aut], Mohammed Sedki [aut], Therese Truong [aut]

GCPBayes_4.2.0.tar.gz
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GCPBayes_4.2.0.tgz(r-4.4-x86_64)GCPBayes_4.2.0.tgz(r-4.4-arm64)GCPBayes_4.2.0.tgz(r-4.3-x86_64)GCPBayes_4.2.0.tgz(r-4.3-arm64)
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GCPBayes.pdf |GCPBayes.html
GCPBayes/json (API)

# Install 'GCPBayes' in R:
install.packages('GCPBayes', repos = c('https://tbaghfalaki.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tbaghfalaki/gcpbayes/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

2.88 score 15 scripts 186 downloads 7 exports 46 dependencies

Last updated 8 months agofrom:631b3714a3. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 10 2024
R-4.5-win-x86_64OKNov 10 2024
R-4.5-linux-x86_64OKNov 10 2024
R-4.4-win-x86_64OKNov 10 2024
R-4.4-mac-x86_64OKNov 10 2024
R-4.4-mac-aarch64OKNov 10 2024
R-4.3-win-x86_64OKNov 10 2024
R-4.3-mac-x86_64OKNov 10 2024
R-4.3-mac-aarch64OKNov 10 2024

Exports:CSDSHSMCMCplotsummaryCSsummaryDSsummaryHS

Dependencies:abindbriocallrclicodacrayondescdiffobjdigestellipseevaluatefftwtoolsfsgdatagluegtoolsHDIntervalinvgammajsonlitelatticelifecyclemagrittrMASSmcmcOutputmcmcsemvtnormpkgbuildpkgloadplotrixpostpackpraiseprocessxpsR6RcppRcppArmadillorlangrprojrootstringistringrtestthattruncnormvctrswaldowiqidwithr