Given individual genotypes of a single SNP, the function checks a population of individuals for Hardy-Weinberg equilibrium.

1 |

`snpG` |
is a column vector in the genotypes array, created by |

`diff` |
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 `diff`

.

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.

`snpSelect`

, `snpRecode`

, `toArray`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
## 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)
# [1] TRUE FALSE FALSE TRUE TRUE FALSE FALSE FALSE TRUE FALSE
``` |

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