mixIndependR (version 0.3.0)

HWE.Chisq: Test the Hardy Weinberg Equilibrium with Chi-square test####

Description

Test the Hardy Weinberg Equilibrium with Chi-square test####

Usage

HWE.Chisq(x,x0,rescale.p=FALSE,simulate.p.value=FALSE,B)

Arguments

x

a matrix of observed genotype frequencies. Each row denotes each genotype; each column denotes each loci. The order of markers follows x; the genotypes are ordered by: from 1:l-th column, the genotypes are homozygous in order as : p1p1, p2p2,p3p3,...,plpl;from ll-th to u-th column, the genotypes are heterozygous in order as:choose(l,2) like: p1p2,p1p3,...,p1pl,p2p3,p2p4,...p2pl,...p(l-1)pl

x0

a matrix of expected Probabilities;each row denotes each genotype; each column denotes each loci. The order of markers follows x; the genotypes are ordered by: from 1:l-th column, the genotypes are homozygous in order as : p1p1, p2p2,p3p3,...,plpl;from ll-th to u-th column, the genotypes are heterozygous in order as:choose(l,2) like: p1p2,p1p3,...,p1pl,p2p3,p2p4,...p2pl,...p(l-1)pl

rescale.p

a logical scalar; if TRUE then p is rescaled (if necessary) to sum to 1. If rescale.p is FALSE, and p does not sum to 1, an error is given.

simulate.p.value

a logical indicating whether to compute p-values by Monte Carlo simulation.

B

an integer specifying the number of replicates used in the Monte Carlo test.

Value

y a list of result of chi-square test, $chi $pvalue; chi and pvalue are vectors of chi square statistics/ p values. Orders follows x.

Details

This function check the Hardy Weinberg Equilibrium from observed and expected distribution with Chi-square test#####

Examples

# NOT RUN {
require(mixIndependR)
x <- data.frame(STR1=c(12,13,13,14,15,13,14,12,14,15),
               STR1_1=c(12,14,13,15,13,14,13,12,14,15),
               SNP1=c("A","T","A","A","T","A","A","T","T","A"),
               SNP1_1=c("A","T","T","T","A","T","A","A","T","T"))
p <- AlleleFreq(x)
g <- GenotypeFreq(x,p,expect=FALSE)
g0 <- GenotypeFreq(x,p,expect=TRUE)
HWE.Chisq(g,g0,rescale.p=FALSE,simulate.p.value=TRUE,2000)
# }