burdenPlot {vbdm} | R Documentation |
This function produces a plot depicting the phenotype distribution, the distribution of carriers of the rare alleles, and also can include the posterior probaiblity of association as estimated by the vbdm algorithm.
burdenPlot(y, G, annotation = rep('missense',ncol(G)), title='', order='mean', legend='keep', type='lines', post=NULL, name.snp=NULL)
y |
A vector of continuous phenotypes. |
G |
A matrix of genotypes that are encoded as 0, 1, or 2. |
annotation |
A vector of SNP annotations for the columns of G. The default is |
title |
An optional title for the plot. |
order |
How the variants should be ordered in the bottom quadrant of the plot. Possible options include |
legend |
If |
type |
If |
post |
Optional vector of posterior probabilities from |
name.snp |
Optional vector of snp names. |
Paul L. Auer (paul.wl.auer@gmail.com), Benjamin A. Logsdon (blogsdon@uw.edu)
Logsdon, B.A., et al. (2014) A Variational Bayes Discrete Mixture Test for Rare Variant Association., Genetic Epidemiology, Vol. 38(1), 21-30 2014
#generate some test data library(vbdm) set.seed(1) n <- 1000 m <- 30 G <- matrix(rbinom(n*m,2,.01),n,m); beta1 <- rbinom(m,1,.2) y <- G%*%beta1+rnorm(n,0,2) res <- vbdm(y=y,G=G,scaling=FALSE); bp<-burdenPlot(y=y,G=G,post=res$pvec,name.snp=1:30);