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Bayesian Network GWAS

This package provides comparably efficient procedures to infer the whole causal graph and estimate the total and direct causal effects from different data sources.

Requirement

We have tested the vignettes under following environment:

R = 4.3.1 pcalg = 2.6-12
Matrix = 1.6-1.1
coop = 0.6-3
graph = 1.80.0
BiocGenerics = 0.48.0 igraph = 1.5.1
dplyr = 1.1.3
glasso = 1.11
glassoFast = 1.0.1 BH =1.84.0.0

In addition, We strongly recommend you to install the pcalg we provided in the Github repository, as we have revise some of the functions provided in the orignal package.

If you are interested in the simulation part, you can refer to this repository for full details: https://github.com/LiangyingYin/BN-GWAS-Simulation

Installation:

library(devtools)
install_github("LiangyingYin/BN-GWAS")

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