Genetics {SpadeR} | R Documentation |
Estimation of genetic differentiation measures
Description
Genetics
: Estimation allelic differentiation among subpopulations based on multiple-subpopulation
genetics data. The richness-based indices include the classic Jaccard and Sorensen dissimilarity
indices; the abundance-based indices include the conventional Gst measure, Horn, Morisita-Horn
and regional species-differentiation indices.
Only Type (1) abundance data (datatype="abundance") is supported; input data for each sub-population
include sample frequencies in an empirical sample of individuals. When there are multiple subpopulations, input data consist of an allele-by-subpopulation frequency matrix.
Usage
Genetics(X, q = 2, nboot = 200)
Arguments
X |
a matrix, or a data.frame of allele frequencies. |
q |
a specified order to use to compute pairwise dissimilarity measures. If |
nboot |
an integer specifying the number of bootstrap replications. |
Value
a list of ten objects:
$info
for summarizing data information.
$Empirical_richness
for showing the observed values of the richness-based dis-similarity indices
including the classic Jaccard and Sorensen indices.
$Empirical_relative
for showing the observed values of the equal-weighted dis-similarity
indices for comparing allele relative abundances including Gst, Horn, Morisita-Horn and regional differentiation measures.
$Empirical_WtRelative
for showing the observed value of the dis-similarity index for
comparing size-weighted allele relative abundances, i.e., Horn size-weighted measure based on Shannon-entropy under equal-effort sampling.
The corresponding three objects for showing the estimated dis-similarity indies are:
$estimated_richness
, $estimated_relative
and $estimated_WtRelative
.
$pairwise
and $dissimilarity.matrix
for showing respectively the pairwise dis-similarity
estimates (with related statistics) and the dissimilarity matrix for various measures depending on
the diversity order q
specified in the function argument.
$q
for showing which diversity order q
to compute pairwise dissimilarity.
References
Chao, A., and Chiu, C. H. (2016). Bridging the variance and diversity decomposition approaches to beta diversity via similarity and differentiation measures. Methods in Ecology and Evolution, 7, 919-928.
Chao, A., Jost, L., Hsieh, T. C., Ma, K. H., Sherwin, W. B. and Rollins, L. A. (2015). Expected Shannon entropy and Shannon differentiation between subpopulations for neutral genes under the finite island model. Plos One, 10:e0125471.
Jost, L. (2008). G_{ST}
and its relatives do not measure differentiation. Molecular Ecology, 17, 4015-4026.
Examples
## Not run:
# Type (1) abundance data
data(GeneticsDataAbu)
Genetics(GeneticsDataAbu,q=2,nboot=200)
## End(Not run)