HierJd: Hierarchical Jaccard dissimilarity

In xinghuq/HierDpart: Partitioning Diversity and Differentiation Across Metrics and Scales, from Genes to Ecosystems

Hierarchical Jaccard dissimilarity

Description

This function calculates hierarchical genetic Jaccard dissimilarity

Usage

HierJd(f, ncode, nreg, r)

Arguments

f	Input file, genepop format
ncode	The integer used to code an allele
nreg	The number of aggregates (regions)
r	The number of subaggregates in each aggregate

Details

This function partitions genetic Jaccard dissimilarity into different hierarchical levels

Value

Jdpop	Jaccard dissimilarity between subaggregates
Jdr	Jaccard dissimilarity between aggregates
HierJd	The partitioning of Jaccard dissimilarity at different hierarchical levels

Author(s)

[e-mail]

References

Qin, X., & Gaggiotti, O. E. (2022). Information-based summary statistics for spatial genetic structure inference. Molecular Ecology Resources, 22(6), 2183-2195.

Jaccard, P. (1901). Etude comparative de la distribution florale dans une portion des Alpes et des Jura. Bull Soc Vaudoise Sci Nat, 37, 547-579.

Jaccard, P. (1912). The distribution of the flora in the alpine zone. 1. New phytologist, 11(2), 37-50.

Examples

f1 <- function(f) system.file("extdata", f,package="HierDpart")
HierJd_Island=HierJd(f1("Island.gen"),nreg=4,r=c(7,4,2,3),ncode=3)
print(HierJd_Island)

xinghuq/HierDpart documentation built on March 21, 2023, 6:43 p.m.