README.md

spinBayes

Travis build
status

Many complex diseases are known to be affected by the interactions between genetic variants and environmental exposures beyond the main genetic and environmental effects. Existing Bayesian methods for G×E interaction studies are challenged by the high-dimensional nature of the study and the complexity of environmental influences. We have developed a novel and powerful semi-parametric Bayesian variable selection method that can accommodate linear and nonlinear G×E interactions simultaneously. Furthermore, the proposed method can conduct structural identification by distinguishing nonlinear interactions from main effects only case within Bayesian framework. Spike-and-slab priors are incorporated on both individual and group level to shrink coefficients corresponding to irrelevant main and interaction effects to zero exactly. The MCMC algorithms of the proposed and alternative methods are efficiently implemented in C++.

How to install

install.packages("devtools")
devtools::install_github("jrhub/spinBayes")

Examples

Example.1 (default method)

library(spinBayes)
data(gExp.L)

test = sample((1:nrow(X2)), floor(nrow(X2)/5))
spbayes=BVCfit(X2[-test,], Y2[-test,], Z2[-test,], E2[-test,], clin2[-test,])
spbayes

selected = BVSelection(spbayes)
selected

pred = predict(spbayes, X2[test,], Z2[test,], E2[test,], clin2[test,], Y2[test,])
pred$pmse
# c(pred$y.pred)

Example.2 (non-structural)

data(gExp.L)

test = sample((1:nrow(X2)), floor(nrow(X2)/5))
spbayes=BVCfit(X2[-test,], Y2[-test,], Z2[-test,], E2[-test,], clin2[-test,], structural=FALSE)
spbayes

selected = BVSelection(spbayes)
selected

pred = predict(spbayes, X2[test,], Z2[test,], E2[test,], clin2[test,], Y2[test,])
pred$pmse
# c(pred$y.pred)

Example.3 (non-sparse)

data(gExp.L)

test = sample((1:nrow(X2)), floor(nrow(X2)/5))
spbayes=BVCfit(X2[-test,], Y2[-test,], Z2[-test,], E2[-test,], clin2[-test,], structural=TRUE, sparse=FALSE)
spbayes

selected = BVSelection(spbayes)
selected

pred = predict(spbayes, X2[test,], Z2[test,], E2[test,], clin2[test,], Y2[test,])
pred$pmse
# c(pred$y.pred)

Methods

This package provides implementation for methods proposed in



Try the spinBayes package in your browser

Any scripts or data that you put into this service are public.

spinBayes documentation built on June 6, 2019, 5:02 p.m.