R: Hardy-Weinberg equlibrium test for a multiallelic marker

hwe {gap} | R Documentation

## 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-squared statistic.
`miss.val` | A list of missing values.

### 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.

### Value

The returned value is a list containing:

allele.freq

  Frequencies of alleles

x2

  Pearson chi-square

p.x2

  p value for chi-square

lrt

  Log-likelihood ratio test statistic

p.lrt

  p value for lrt

df

  Degree(s) of freedom

rho

  sqrt{chi-square/N} the contingency table coefficient

### Author(s)

Jing Hua Zhao

### 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

    ## End(Not run)

[Package gap version 1.2.3-6 Index]