Hardy-Weinberg equilibrium test using MCMC
Hardy-Weinberg equilibrium test by MCMC
hwe.hardy(a, alleles = 3, seed = 3000, sample = c(1000, 1000, 5000))
a |
an array containing the genotype counts, as integer. |
alleles |
number of allele at the locus, greater than or equal to 3, as integer |
seed |
pseudo-random number seed, as integer. |
sample |
optional, parameters for MCMC containing number of chunks, size of a chunk and burn-in steps, as integer. |
The returned value is a list containing:
method |
Hardy-Weinberg equilibrium test using MCMC |
data.name |
name of used data if |
p.value |
Monte Carlo p value |
p.value.se |
standard error of Monte Carlo p value |
switches |
percentage of switches (partial, full and altogether) |
Guo, S.-W. and E. A. Thompson (1992) Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics. 48:361–372.
Adapted from HARDY, testable with -Dexecutable as standalone program
Sun-Wei Guo, Jing Hua Zhao, Gregor Gorjanc
http://www.stat.washington.edu/thompson/Genepi/pangaea.shtml,
## Not run:
# example 2 from hwe.doc:
a<-c(
3,
4, 2,
2, 2, 2,
3, 3, 2, 1,
0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 1,
0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 2, 1, 0, 0, 0)
ex2 <- hwe.hardy(a=a,alleles=8)
# example using HLA
data(hla)
x <- hla[,3:4]
y <- pgc(x,handle.miss=0,with.id=1)
n.alleles <- max(x,na.rm=TRUE)
z <- vector("numeric",n.alleles*(n.alleles+1)/2)
z[y$idsave] <- y$wt
hwe.hardy(a=z,alleles=n.alleles)
# with use of class 'genotype'
# this is to be fixed
library(genetics)
hlagen <- genotype(a1=x$DQR.a1, a2=x$DQR.a2,
alleles=sort(unique(c(x$DQR.a1, x$DQR.a2))))
hwe.hardy(hlagen)
# comparison with hwe
hwe(z,data.type="count")
# to create input file for HARDY
print.tri<-function (xx,n) {
cat(n,"\n")
for(i in 1:n) {
for(j in 1:i) {
cat(xx[i,j]," ")
}
cat("\n")
}
cat("100 170 1000\n")
}
xx<-matrix(0,n.alleles,n.alleles)
xxx<-lower.tri(xx,diag=TRUE)
xx[xxx]<-z
sink("z.dat")
print.tri(xx,n.alleles)
sink()
# now call as: hwe z.dat z.out
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