gap (version 0.8-2)

hwe: Hardy-Weinberg equlibrium test

Description

Hardy-Weinberg equilibrium test

Usage

hwe(data,yates.correct=FALSE, miss.val=0)
hwe(data,is.genotype=FALSE, yates.correct=FALSE, miss.val=0)
hwe(data,is.count=FALSE, yates.correct=FALSE, miss.val=0)

Arguments

data

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

is.genotype

A flag indicating if the data is an array of genotypes

is.count

A flag indicating if the data is an array of genotypes 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:
• 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
  $\chi^2/N$ the effect size

synopsis

hwe(data, is.count=FALSE, is.genotype=FALSE, yates.correct=FALSE, miss.val=0)

Details

This function obtains Hardy-Weinberg equilibrium test statistics. It can handle data coded as allele numbers (default), genotype identifiers (by setting is.genotype=TRUE) and counts corresponding to individual genotypes (by setting is.count=TRUE) ; the latter does not need is.genotype to be specified but requires that genotype counts for all possible genotypes, i.e. n(n+1)/2, where n is the number of alleles.

See Also

hwe.hardy

Examples

a <- c(3,2,2)
a.out <- hwe(a,is.genotype=TRUE)
a.out
a.out <- hwe(a,is.count=TRUE)
a.out