prabclus: phipt – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

phipt

Distances between communities, auxiliary functions

Description

Auxiliary functions for communitydist. phipt computes phiPT/phiST (Peakall and Smouse, 2012, Meirmans, 2006) between two communities. cfchord computes the chord-distance (Cavalli-Sforza and Edwards, 1967) between two lists or locus-wise relative allele frequencies. shared.problist computes a straightforward generalisation of the shared allele distance (Bowcock et al., 1994) between individuals for communities, namely the ‘overlap’, i.e., sum of the minima of the allele relative frequencies. diploidcomlist constructs the input lists for cfchord and shared.problist from an alleleobject. It provides relative frequencies for all alles of all loci in all communities.

Usage

phipt(alleleobj,comvector,i,j)
cfchord(p1,p2)
shared.problist(p1,p2)
diploidcomlist(alleleobj,comvector,diploid=TRUE)

Arguments

`alleleobj`	if `diploid=TRUE`, an object of class `alleleobject` as produced by function `alleleinit`. This has the required information on the individuals that are grouped into communities. In case `diploid=FALSE`, a list that needs to have components `n.variables` (number of loci), `alevels` (vector of allele names, see `alleleinit`) and `charmatrix` (matrix of characters with one row for every individual and one column for every locus giving the alleles; see examples below for how this can be constructed for a `prabobject` with presence-absence data).
`comvector`	vector of integers indicating to which community an individual belongs.
`i`	integer. Number of community.
`j`	integer. Number of community. The phiPT-distance is computed between the communities numbered `i` and `j`
`p1`	list. Every list entry refers to a locus and is a vector of relative frequencies of the alleles present in that locus in a community.
`p2`	list. Every list entry refers to a locus and is a vector of relative frequencies of the alleles present in that locus in a community. The chord or shared allele distance is computed between the communities encoded by `p1` and `p2`.
`diploid`	logical, indicating whether loci are diploid, see `alleleobj`.

Value

cfchord gives out the value of the chord distance. shared.problist gives out the distance value. diploidcomlist gives out a two-dimensional list. The list has one entry for each community, which is itself a list. This community list has one entry for each locus, which is a vector that gives the relative frequencies of the different alleles in phipt gives out a list with components phipt, vap, n0, sst, ssg, msa, msw. These refer to the notation on p.2.12 and 2.15 of Peakall and Smouse (2012).

`phipt`	value of phiPT.
`vap`	variance among (between) populations (communities).
`n0`	standardisation factor N0, see p.2.12 of Peakall and Smouse (2012).
`sst`	total distances sum of squares.
`ssg`	vector with two non-`NA` entriesm, within community sums of squares for communities `i` and `j`.
`msa`	mean square between communities.
`msw`	mean square within communities.

Author(s)

Christian Hennig christian.hennig@unibo.it https://www.unibo.it/sitoweb/christian.hennig/en

References

Bowcock, A. M., Ruiz-Linares, A., Tomfohrde, J., Minch, E., Kidd, J. R., Cavalli-Sforza, L. L. (1994) High resolution of human evolutionary trees with polymorphic microsatellites. Nature 368, 455-457.

Cavalli-Sforza, L. L. and Edwards, A. W. F. (1967) Phylogenetic Analysis - Models and Estimation Procedures. The American Journal of Human Genetics 19, 233-257.

Meirmans, P. G. (2006) Using the AMOVA framework to estimate a standardized genetic differentiation measure. Evolution 60, 2399-2402.

Peakall, R. and Smouse P.E. (2012) GenAlEx Tutorial 2. https://biology-assets.anu.edu.au/GenAlEx/Tutorials.html

Examples

options(digits=4)
  data(tetragonula)
  tnb <-
  coord2dist(coordmatrix=tetragonula.coord[83:120,],cut=50,file.format="decimal2",neighbors=TRUE)
  ta <- alleleconvert(strmatrix=tetragonula[83:120,])
  tai <- alleleinit(allelematrix=ta,neighborhood=tnb$nblist)
  tetracoms <-
  c(rep(1:3,each=3),4,5,rep(6:11,each=2),12,rep(13:19,each=2))
  phipt(tai,tetracoms,4,6)
  tdip <- diploidcomlist(tai,tetracoms,diploid=TRUE)
  cfchord(tdip[[4]],tdip[[6]])
  shared.problist(tdip[[4]],tdip[[6]])

prabclus

Functions for Clustering and Testing of Presence-Absence, Abundance and Multilocus Genetic Data

v2.3-2

GPL

Authors

Christian Hennig <christian.hennig@unibo.it>, Bernhard Hausdorf <Hausdorf@zoologie.uni-hamburg.de>

Initial release

2020-01-06