CPBayes {CPBayes} | R Documentation |

## CPBayes: An R-package implemeting a Bayesian meta analysis method for studying cross-phenotype genetic associations.

### Description

Simultaneous analysis of genetic associations with multiple phenotypes may reveal shared genetic susceptibility across traits (pleiotropy). CPBayes is 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.

### Details

The package consists of following functions:
`analytic_locFDR_BF_uncor`

, `cpbayes_uncor`

; `analytic_locFDR_BF_cor`

, `cpbayes_cor`

; `post_summaries`

, `forest_cpbayes`

, `estimate_corln`

.

### Functions

`analytic_locFDR_BF_uncor`

It analytically computes the local FDR (locFDR) and Bayes factor (BF) quantifying the evidence of aggregate-level pleiotropic association for uncorrelated summary statistics.

`cpbayes_uncor`

It implements CPBayes (based on MCMC) for uncorrelated summary statistics to figure out the optimal subset of non-null traits underlying a pleiotropic signal and other insights. The summary statistics across traits/studies are uncorrelated when the studies have no overlapping/genetically related subjects.

`analytic_locFDR_BF_cor`

It analytically computes the local FDR (locFDR) and Bayes factor (BF) for correlated summary statistics.

`cpbayes_cor`

It implements CPBayes (based on MCMC) for correlated summary statistics to figure out the optimal subset of non-null traits underlying a pleiotropic signal and other insights. The summary statistics across traits/studies are correlated when the studies have overlapping/genetically related subjects or the phenotypes were measured in a cohort study.

`post_summaries`

It summarizes the MCMC data produced by

`cpbayes_uncor`

or`cpbayes_cor`

. It computes additional summaries to provide a better insight into a pleiotropic signal. It works in the same way for both`cpbayes_uncor`

and`cpbayes_cor`

.`forest_cpbayes`

It creates a forest plot presenting the pleiotropy result obtained by

`cpbayes_uncor`

or`cpbayes_cor`

. It works in the same way for both`cpbayes_uncor`

and`cpbayes_cor`

.`estimate_corln`

It computes an approximate correlation matrix of the beta-hat vector for multiple overlapping case-control studies using the sample-overlap count matrices.

### References

Majumdar A, Haldar T, Bhattacharya S, Witte JS (2018) An efficient Bayesian meta analysis approach for studying cross-phenotype genetic associations. PLoS Genet 14(2): e1007139.

*CPBayes*version 1.1.0 Index]