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VIMCO performs a Bayesian variable selection for GWAS data with multiple traits, while accounting for correlation among the multiple traits.

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vimco

vimco package proves a Bayesian variable selection method for GWAS data with multiple traits. Unlike in BVSR where each trait is analyzed seperately, vimco performs a joint analysis for the multiple traits, while accounting for correlation among the multiple traits.

Installation

To install the development version of vimco, it's easiest to use the 'devtools' package. Note that vimco depends on the 'Rcpp' package, which also requires appropriate setting of Rtools and Xcode for Windows and Mac OS/X, respectively.

library(devtools)
install_github("XingjieShi/VIMCO")

Usage

library(vimco)
?vimco

Replicate simulation results in Shi et al. (2018)

All the simulation results can be reproduced by using the code at simulation. Before running simulation to reproduce the results, please familarize yourself with vimco using 'VIMCO' vignette. Simulation results can be reproduced by following steps in the vimco vignette.

Reference

VIMCO: Variational Inference for Multiple Correlated Outcomes in Genome-wide Association Studies

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VIMCO performs a Bayesian variable selection for GWAS data with multiple traits, while accounting for correlation among the multiple traits.

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