Package: CPBayes 1.1.0

CPBayes: Bayesian Meta Analysis for Studying Cross-Phenotype Genetic Associations

A Bayesian meta-analysis method for studying cross-phenotype genetic associations. It uses summary-level data across multiple phenotypes to simultaneously measure the evidence of aggregate-level pleiotropic association and estimate an optimal subset of traits associated with the risk locus. CPBayes is based on a spike and slab prior. The methodology is available from: A Majumdar, T Haldar, S Bhattacharya, JS Witte (2018) <doi:10.1371/journal.pgen.1007139>.

Authors:Arunabha Majumdar <[email protected]> [aut, cre], Tanushree Haldar <[email protected]> [aut], John Witte [ctb]

CPBayes_1.1.0.tar.gz
CPBayes_1.1.0.zip(r-4.5)CPBayes_1.1.0.zip(r-4.4)CPBayes_1.1.0.zip(r-4.3)
CPBayes_1.1.0.tgz(r-4.5-any)CPBayes_1.1.0.tgz(r-4.4-any)CPBayes_1.1.0.tgz(r-4.3-any)
CPBayes_1.1.0.tar.gz(r-4.5-noble)CPBayes_1.1.0.tar.gz(r-4.4-noble)
CPBayes_1.1.0.tgz(r-4.4-emscripten)CPBayes_1.1.0.tgz(r-4.3-emscripten)
CPBayes.pdf |CPBayes.html
CPBayes/json (API)
NEWS

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

Bug tracker:https://github.com/arunabhacodes/cpbayes/issues

Datasets:

On CRAN:

4.26 score 3 stars 12 scripts 294 downloads 1 mentions 7 exports 13 dependencies

Last updated 4 years agofrom:4df15cb9d3. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 01 2025
R-4.5-winOKFeb 01 2025
R-4.5-macOKFeb 01 2025
R-4.5-linuxOKFeb 01 2025
R-4.4-winOKFeb 01 2025
R-4.4-macOKFeb 01 2025
R-4.3-winOKFeb 01 2025
R-4.3-macOKFeb 01 2025

Exports:analytic_locFDR_BF_coranalytic_locFDR_BF_uncorcpbayes_corcpbayes_uncorestimate_corlnforest_cpbayespost_summaries

Dependencies:abindbackportscheckmatecliforestplotgluelifecyclemagrittrMASSmvtnormpurrrrlangvctrs

CPBayes (Bayesian meta analysis for studying cross-phenotype genetic associations) package

Rendered fromcpbayes.Rmdusingknitr::rmarkdownon Feb 01 2025.

Last update: 2020-12-01
Started: 2017-01-23