Description Usage Arguments Details Value Author(s) Examples
View source: R/posterior_prob_functions.R
Posterior probabilities of causality from P-values
1 |
pvals |
P-values 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) |
This function converts p-values to posterior probabilities of causality, including the null model of no genetic effect
Posterior probabilities of null model (no genetic effect) and causality for each SNP
Anna Hutchinson
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | set.seed(1)
nsnps = 100
N0 = 5000
N1 = 5000
z_scores <- rnorm(nsnps, 0, 3)
p_values <- 2 * pnorm( - abs ( z_scores ) )
## 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 <- pvals_pp(pvals = p_values, f = maf, type = "cc", N = N0+N1, s = N1/(N0+N1))
sum(res)
res
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.