Test influence of samples on Hardy-Weinberg equilibrium via jackknife.
jackHWE(g, exclude.num = 1, min.hwe.samples = 5, show.progress = TRUE,
use.genepop = FALSE, ...)jackInfluential(jack.result, alpha = 0.05)
# S3 method for jack.influential
plot(x, main = NULL, ...)
Number of samples to exclude at a time.
minimum samples needed to calculate HWE.
logical. Show progress of jackknife?
logical. Use GENEPOP to calculate HWE p-values? If FALSE
then hw.test is used.
other arguments to be passed to GENEPOP.
result from run of jackHWE.
critical value to determine if exclusion is "influential".
result from a call to jackInfluential.
main title for influential sample plots from
plot.jack.influential.
jackHWE returns a list with:
a named vector of HWE p-values for each locus.
a data.frame of HWE p-values where each row is an
exclusion and columns are loci.
the original gtypes object.
a data.frame of influential exclusions.
a data.frame listing the allele frequencies of
influential exclusions.
a matrix of odds ratios between exclusions (rows)
and loci (columns).
jackHWEperforms a HWE jackknife where all combinations
of exclude.num samples are left out and HWE is recalculated
jackInfluentialcalculates odds.ratios between jackknife
HWE and observed HWE and identifies "influential" samples. Samples
are "influential" if the observed HWE p-value is < alpha, but
is > alpha when the samples are not present
plot.jack.influentialcreates a cumulative frequency plot
of all odds-ratios from jack.influential. A vertical dashed
line marks the smallest influential exclusion
Morin, P.A., R.G. LeDuc, F.I. Archer, K.K. Martien, R. Huebinger, J.W. Bickham, and B.L. Taylor. 2009. Significant deviations from Hardy-Weinberg equilibirum caused by low levels of microsatellite genotyping errors. Molecular Ecology Resources 9:498-504.