popStructTest | R Documentation |
Conduct multiple tests of population structure / differentiation.
Overall tests can be conducted for the current stratification scheme
(overallTest()
), or can be conducted for all unique
pairs of strata (pairwiseTest()
). All statistics appropriate to
the ploidy of the data are estimated at once. See Note
for a
description of each statistic.
overallTest(
g,
nrep = 1000,
by.locus = FALSE,
hap.locus = 1,
quietly = FALSE,
max.cores = 1,
...
)
pairwiseTest(
g,
nrep = 1000,
by.locus = FALSE,
hap.locus = 1,
quietly = FALSE,
max.cores = 1,
...
)
pairwiseMatrix(pws, stat, locus = "All")
pairwiseSummary(pws, locus = "All")
g |
a |
nrep |
number specifying number of permutation replicates to use for permutation test. |
by.locus |
return by-locus values of statistics? If |
hap.locus |
which locus to use if |
quietly |
logical. print progress to screen? |
max.cores |
the maximum number of cores to use to distribute replicates
for permutation tests over. If set to |
... |
parameters passed to |
pws |
a list returned from a call to |
stat |
the name of a statistic in the |
locus |
the name of a single locus. If |
overallTest()
a list containing:
strata.freq
a table of the sample sizes for each stratum
result
an array with the statistic estimate and p-value
for each statistic. If by.locus = FALSE
or g
is a haploid dataset,
this is a two-dimensional array, with one row per statistic,
statistic estimate in the first column and permutation test p-value
in the second column. If by.locus = TRUE
and g
has ploidy > 1,
then this is a three-dimensional array where the first dimension
is loci, second dimension is statistics, and third dimension is
statistic estimate and p-value.
pairwiseTest()
a list containing a list of results as described above
for overallTest()
for each pairwise comparison.
pairwiseMatrix()
a matrix summarizing a chosen statistic
(stat
) for a chosen locus (locus
) between pairs of strata
with the statistic estimate in the lower left and the p-value in the upper right.
pairwiseSummary()
a data frame summarizing all pairwise statistics and p-values along with strata sample sizes.
The computed statistics are:
CHIsq | chi-squared estimate measuring random allele frequency distribution distributed across strata (haploid and diploid) |
Ho, Hs, Ht | Nei and Kumar 2002 :
observed heterozygosity (Ho ),
within population diversity (Hs ), overall diversity (Ht )
|
Ht_prime | description |
Dst | description |
Dst_prime | description |
Fst | For haploid data, equivalent to PHIst with pairwise distances set to 1. For diploid data, |
Fst_prime | description |
Fis | description |
Gst_prime | description |
Gst_dbl_prime | description |
Dest, Dest_Chao | population differentiation (Jost 2008) |
wcFit, wcFst, wcFit | (Weir and Cockerham 1984) |
PHIst | Haploid AMOVA estimate of differentiation derived
from matrix of pairwise distances between sequences.
See dist.dna for details on distance computation.
(Excoffier et al 1992) |
Eric Archer eric.archer@noaa.gov
Excoffier, L., Smouse, P.E. and Quattro, J.M. 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131:479–491. Jost, L. 2008. GST and its relatives do not measure differentiation. Molecular Ecology 17:4015-4026. Nei M. and Chesser R. 1983. Estimation of fixation indexes and gene diversities. Annals of Human Genetics 47:253-259. Nei M. 1987. Molecular Evolutionary Genetics. Columbia University Press Weir, B.S. and Cockerham, C.C. 1984. Estimating F-statistics for the analysis of population structure. Evolution 38:1358–1370. Weir, B.S. and Hill, W.G. 2002. Estimating F-statistics. Annual Review of Genetics 36:721–750.
basic.stats
, Fst
,
amova
# An overall test with microsatellite data
data(msats.g)
ovl <- overallTest(msats.g, nrep = 100)
ovl
#' A pairwise test with control region sequences
data(dloop.g)
pws <- pairwiseTest(dloop.g, nrep = 100)
pws
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