Given individual genotypes of a single SNP, the function checks a population of individuals for Hardy-Weinberg equilibrium.
is a column vector in the genotypes array, created by
heterozygosity difference used in HW equilibrium, see ‘Details’.
A logical function to check for HW equilibrium, the expected frequency of the heterozygous
genotype is estimated based on the two homozygous genetypes by ‘sqrt(4*p^2*q^2)’.
The absolute difference between the expected and observed frequency of the heterozygous
genotype of the SNP needs to be smaller than the minimum difference of
A logical TRUE for H-W equilibrium or FALSE for H-W disequilibrium is returned.
Falconer and Mackay (1996). Introduction to Quantitative Genetics (4th Edition). Pearson Education Limited, Edinburgh, England.
Wiggans et al. (2009). Selection of single-nucleotide polymorphisms and quality of genotypes used in genomic evaluation of dairy cattle in the United States and Canada. Journal of Dairy Science, 92, 3431-3436.
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## Simulate random allele designations for 100 bi-allelic SNPs set.seed(2016) desig <- array(sample(c('A','C','G','T'), size = 200, repl = TRUE), dim=c(100, 2)) ## Simulate random SNP genotypes for 20 individuals - put them in array format ## '-' indicates an unknown base ga <- array(0, dim=c(20, 100)) for(i in 1:20) for(j in 1:100) ga[i, j] <- paste(sample(c(desig[j,],"-"), 2, prob=c(.47, .47, .06), repl = TRUE), collapse='') ## Recode the matrix, place recoded genotypes in ga.r desig <- data.frame(AlleleA_Forward = factor(desig[,1]), AlleleB_Forward = factor(desig[,2])) ga.r <- array(5, dim=c(20, 100)) for(i in 1:100) ga.r[,i] <- snpRecode(ga[,i], desig[i,]) ## Check the first 10 SNPs for H-W equilibrium based on a minimum ## allowed difference of 0.15 between observed and expected heterozygosity apply(ga.r[,1:10], 2, is.hwEq, diff=.15) #  TRUE FALSE FALSE TRUE TRUE FALSE FALSE FALSE TRUE FALSE
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