# Distances between communities 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. ```r communitydist(alleleobj,comvector="auto",distance="chord", compute.geodist=TRUE,out.dist=FALSE, grouping=NULL,geodist=NA,diploid=TRUE, phiptna=NA,...) ``` ## 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`. ## 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). ## Returns 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. ## 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](https://biology-assets.anu.edu.au/GenAlEx/Tutorials.html) ## Author(s) Christian Hennig christian.hennig@unibo.it [https://www.unibo.it/sitoweb/christian.hennig/en](https://www.unibo.it/sitoweb/christian.hennig/en) ## 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 ```r 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) ```

communitydist function