GCPBayes: GCPBayes Package

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

GCPBayes Package

Description

Run a Gibbs sampler for a multivariate Bayesian sparse group selection model with Dirac, continuous and hierarchical spike prior for detecting pleiotropic effects on multiple traits. This package is designed for summary statistics containing estimated regression coefficients and their estimated covariance matrices.

Author(s)

Taban Baghfalaki [e-mail], [e-mail]

References

1. Baghfalaki, T., Sugier, P. E., Truong, T., Pettitt, A. N., Mengersen, K., & Liquet, B. (2021). Bayesian meta analysis models for cross cancer genomic investigation of pleiotropic effects using group structure. Statistics in Medicine, 40(6), 1498-1518.

2. Baghfalaki, T., Sugier, Y. Asgari, P. E., Truong, & Liquet, B. (2021). GCPBayes: An R Package for Studying Cross-Phenotype Genetic Associations with Group-Level Bayesian Meta-Analysis. Submitted.

GCPBayes documentation built on May 29, 2024, 3:30 a.m.