Compute the population observed heterozygosity
pop_het_obs.RdThis function computes population heterozygosity, using the formula of Nei (1987).
Usage
pop_het_obs(
.x,
by_locus = FALSE,
include_global = FALSE,
n_cores = bigstatsr::nb_cores()
)Arguments
- .x
a
gen_tibble(usually grouped, as obtained by usingdplyr::group_by(), otherwise the full tibble will be considered as belonging to a single population).- by_locus
boolean, determining whether Ho should be returned by locus(TRUE), or as a single genome wide value (FALSE, the default).
- include_global
boolean determining whether, besides the population specific estiamtes, a global estimate should be appended. Note that this will return a vector of n populations plus 1 (the global value), or a matrix with n+1 columns if
by_locus=TRUE.- n_cores
number of cores to be used, it defaults to
bigstatsr::nb_cores()
Value
a vector of mean population observed heterozygosities (if by_locus=FALSE), or a matrix of
estimates by locus (rows are loci, columns are populations, by_locus=TRUE)
Details
Within population observed heterozygosity \(\hat{h}_o\) for a locus with \(m\) alleles is defined as:
\(\hat{h}_o= 1-\sum_{k=1}^{s} \sum_{i=1}^{m} \hat{X}_{kii}/s\)
where
\(\hat{X}_{kii}\) represents the proportion of homozygote \(i\) in the sample for the \(k\)th population and
\(s\) the number of populations,
following equation 7.38 in Nei(1987) on pp.164. In our specific case, there are only two alleles, so \(m=2\). For
population specific estimates, the sum is done over a single value of \(k\). \(\hat{h}_o\) at
the genome level is simply the mean of the locus estimates.