z0_pp {corrcoverage} | R Documentation |
Find PPs for SNPs and null model from Z-scores and MAFs
Description
Posterior probabilities of causality from marginal Z-scores with prior SD as a parameter
Usage
z0_pp(z, f, type, N, s, W = 0.2, p1 = 1e-04)
Arguments
z |
Marginal Z-scores of SNPs |
f |
Minor allele frequencies |
type |
Type of experiment ('quant' or 'cc') |
N |
Total sample size |
s |
Proportion of cases (N1/N0+N1), ignored if type=='quant' |
W |
Prior for the standard deviation of the effect size parameter, beta (default 0.2) |
p1 |
Prior probability a SNP is associated with the trait (default 1e-4) |
Details
Converts Z-scores to posterior probabilities of causality, including the null model of no genetic effects
Value
Posterior probabilities of null model (no genetic effect) and causality for each SNP
Author(s)
Anna Hutchinson
Examples
set.seed(1)
nsnps = 100
N0 = 5000
N1 = 5000
z_scores <- rnorm(nsnps, 0, 3)
## generate example LD matrix and MAFs
library(mvtnorm)
nsamples = 1000
simx <- function(nsnps, nsamples, S, maf=0.1) {
mu <- rep(0,nsnps)
rawvars <- rmvnorm(n=nsamples, mean=mu, sigma=S)
pvars <- pnorm(rawvars)
x <- qbinom(1-pvars, 1, maf)
}
S <- (1 - (abs(outer(1:nsnps,1:nsnps,`-`))/nsnps))^4
X <- simx(nsnps,nsamples,S)
maf <- colMeans(X)
res <- z0_pp(z = z_scores, f = maf, type = "cc", N = N0+N1, s = N1/(N0+N1))
sum(res)
res
[Package corrcoverage version 1.2.1 Index]