gap (version 1.2.3-1)

hwe: Hardy-Weinberg equlibrium test for a multiallelic marker

Description

Hardy-Weinberg equilibrium test

Usage

hwe(data, data.type="allele", yates.correct=FALSE, miss.val=0)

Arguments

data

A rectangular data containing the genotype, or an array of genotype counts

data.type

An option taking values "allele", "genotype", "count" if data is alleles, genotype or genotype count

yates.correct

A flag indicating if Yates' correction is used for Pearson \(\chi^2\) statistic

miss.val

A list of missing values

Value

The returned value is a list containing:

allele.freq

Frequencies of alleles

x2

Pearson \(\chi^2\)

p.x2

p value for \(\chi^2\)

lrt

Log-likelihood ratio test statistic

p.lrt

p value for lrt

df

Degree(s) of freedom

rho

\(\sqrt{\chi^2/N}\) the contingency table coefficient

Details

This function obtains Hardy-Weinberg equilibrium test statistics. It can handle data coded as allele numbers (default), genotype identifiers (by setting data.type="genotype") and counts corresponding to individual genotypes (by setting data.type="count") which requires that genotype counts for all n(n+1) possible genotypes, with n being the number of alleles.

For highly polymorphic markers when asymptotic results do not hold, please resort to hwe.hardy.

See Also

hwe.hardy

Examples

# NOT RUN {
a <- c(3,2,2)
a.out <- hwe(a,data.type="genotype")
a.out
a.out <- hwe(a,data.type="count")
a.out
require(haplo.stats)
data(hla)
hla.DQR <- hwe(hla[,3:4])
summary(hla.DQR)
# multiple markers
s <- vector()
for(i in seq(3,8,2))
{
  hwe_i <- hwe(hla[,i:(i+1)])
  s <- rbind(s,hwe_i)
}
s
# }