Description Usage Arguments Value References Examples

`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.

1 |

`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. |

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.

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.

1 2 3 4 5 6 | ```
## Not run:
# Type (1) abundance data
data(GeneticsDataAbu)
Genetics(GeneticsDataAbu,q=2,nboot=200)
## End(Not run)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.