prabclus (version 2.3-4)

communitydist: Distances between communities

Description

Constructs distances between communities: chord- (Cavalli-Sforza and Edwards, 1967), phiPT/phiST (Peakall and Smouse, 2012, Meirmans, 2006), three versions of the shared allele distance between communities, and geographical distance between communities.

Usage

communitydist(alleleobj,comvector="auto",distance="chord",
                          compute.geodist=TRUE,out.dist=FALSE,
                          grouping=NULL,geodist=NA,diploid=TRUE,
                          phiptna=NA,...)

Value

list with components

comvector

integer vector of length of the number of individuals, indicating their community membership.

dist

genetic distances between communities. Parameter out.dist determines whether this is a dist-object or a matrix.

cgeodist

if compute.geodist, geographical distance between communities defined as average distance of all pairs of individuals belonging to different ones of the two communities between which the distance is computed. Parameter out.dist determines whether this is a dist-object or a matrix.

comgroup

vector of length of the number of communities. If grouping was provided, this is a vector giving the group memberships of all communities, otherwise it is a vector of 1s.

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

either a vector of integers indicating to which community an individual belongs (these need to be numbered from 1 to a maximum number without interruption), or "auto", which indicates that communities are automatically generated by the communities-function.

distance

one of "chord", "phipt", "shared.average", "shared.chakraborty", "shared.problist". See Details.

compute.geodist

logical, indicating whether geographical distances between communities should be generated.

out.dist

logical, indicating whether dist-objects are given out or rather distance matrices.

grouping

something that can be coerced into a factor, for passing on to communities in case that comvector=="auto". This implies that individuals in different groups indicated by grouping cannot be together in the same community. Furthermore (also if comvector is something else), a vector of groups of communities will be computed, see output component comgroup. In any case individuals in different groups are not allowed to be in the same community.

geodist

matrix or dist-object providing geographical distances between individuals. Required if compute.geodist==TRUE or comvector=="auto".

diploid

logical, indicating whether loci are diploid, see alleleobj.

phiptna

if distance="phipt", value to be given out as phiPT-distance in case that the original definition amounts to 0/0 (particularly if communities have just one member).

...

optional arguments to be passed on to communities.

Author

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

Details

All genetic distances between communities are based on the information given in alleleobj; either on the alleles directly or on a genetic distance (distmat-component, see alleleinit). The possible genetic distance measures between communities are as follows:

• "chord": chord-distance (Cavalli-Sforza and Edwards, 1967)

• "phipt": phiPT-distance implemented according to Peakall and Smouse, 2012. This also appears in the literature under the name phiST (Meirmans, 2006, although the definition there is incomplete and we are not sure whether this is identical).

• "shared.average": average of between-community genetic distances.

• "shared.chakraborty": between-community shared allele distance according to Chakraborty and Jin (1993).

• "shared.problist": this implements the shared allele distance (Bowcock et al., 1994) for individuals directly for communities (one minus proportion of alleles shared by two communities averaged over loci).

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.

Chakraborty, R. and Jin, L. (1993) Determination of relatedness between individuals using DNA fingerprinting. Human Biology 65, 875-895.

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

See Also

communities; refer to phipt for computation of distances between specific pairs of communities. diploidcomlist produces relative frequencies for all alles of all loci in all communities (on which the chord- and the "shared.problist"-distances are based).

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$nblist)
  tetraspec <- c(rep(1,11),rep(2,13),rep(3,14))
  tetracoms <-
  c(rep(1:3,each=3),4,5,rep(6:11,each=2),12,rep(13:19,each=2))
  c1 <- communitydist(tai,comvector=tetracoms,distance="chord",
    geodist=tnb$distmatrix,grouping=tetraspec)
  c2 <- communitydist(tai,comvector=tetracoms,distance="phipt",
    geodist=tnb$distmatrix,grouping=tetraspec,compute.geodist=FALSE)
  c3 <- communitydist(tai,comvector=tetracoms,distance="shared.average",
    geodist=tnb$distmatrix,grouping=tetraspec,compute.geodist=FALSE)
  c4 <- communitydist(tai,comvector=tetracoms,distance="shared.chakraborty",
    geodist=tnb$distmatrix,grouping=tetraspec,compute.geodist=FALSE)
  c5 <- communitydist(tai,comvector=tetracoms,distance="shared.problist",
    geodist=tnb$distmatrix,grouping=tetraspec,compute.geodist=FALSE)
  round(c1$cgeodist,digits=1)
  c1$comvector
  c2$comvector
  c3$comvector
  c4$comvector
  c5$comvector
  round(c1$dist,digits=2)
  round(c2$dist,digits=2)
  round(c3$dist,digits=2)
  round(c4$dist,digits=2)
  round(c5$dist,digits=2)