Description Usage Arguments Value Examples
View source: R/Fun_mix_EM_15Jan2018_marg_lik.R
calculate BF with mixture prior.
1 |
obs.data |
N*2 data matrix, N is the sample size, 1st column is sum of rare variants for each individual, 2nd column is the disease status |
nvariants |
number of sites of the region |
low.bound |
lower bound |
Vector of 3 elements. 1st, probability of p=0; 2nd, precision parameter of beta distribution,3rd: BF
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 26 27 28 | nsites = 500
ncase = 200
ncontrol = 200
maf = 0.005
rexp_param = 2
model1 = function(i) {
p1 = rbinom( ncontrol , nsites , maf )
p2 = rbinom( ncase , nsites , maf ) + H1 * round(rexp(ncase,rexp_param))
disease_status = c ( rep(0,ncontrol),rep(1,ncase) )
data = data.frame(c(p1,p2), disease_status)
bf = BFmixture(data, nsites)[3]
bf
}
nrep = 20
H1 = 0
bf1 = ( replicate(nrep,model1() ) )
H1 = 1
bf2 = ( replicate(nrep,model1() ) )
col = c( rep("blue",nrep) , rep("red", nrep))
plot(log(c(bf1,bf2)),col = col ,pch=20,cex=1.5)
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