lociplots: Visualises clusters of markers vs. species

Description

Given a clustering of individuals from prabclust (as generated in species delimitation) and a clustering of markers (for example dominant markers of genetic loci), lociplots visualises the presence of markers against the clustering of individuals and computes some statistics.

Usage

lociplots(indclust,locclust,locprab,lcluster,
                      symbols=NULL,brightest.grey=0.8,darkest.grey=0,
                      mdsdim=1:2)

Arguments

indclust

prabclust-object. Clustering of individuals.

locclust

vector of integers. Clustering of markers/loci.

locprab

prab-object in which the markers are what the help page of prabinit refers to as "species" (i.e., reverse of what is used for species delimitation clus

lcluster

integer. Number of cluster in locclust for which plot and statistics are produced.

symbols

vector of plot symbols. If NULL, indclust$symbols is used.

brightest.grey

numeric between 0 and 1. Brightest grey value used in plot for individuals with smallest marker percentage, see details.

darkest.grey

numeric between 0 and 1. Darkest grey value used in plot for individuals with highest marker percentage, see details.

mdsdim

vector of two integers. The two MDS variables taken from indclust used for visualisation.

Value

list with components
locfreqvector of individual marker percentages.
locfreqminvector of minimum individual marker precentages for each cluster in indclust-clustering (the first value refers to the "noise component", if present).
locfreqmaxvector of maximum individual marker precentages for each cluster in indclust-clustering (the first value refers to the "noise component", if present).
locfreqmeanvector of average individual marker precentages for each cluster in indclust-clustering (the first value refers to the "noise component", if present).

Details

Plot and statistics are based on the individual marker percentage, which is the percentage of markers present in an individual of the markers belonging to cluster no. lcluster. In the plot, the grey value visualises the marker percentage.

Examples

Run this code

data(veronica)
  vei <- prabinit(prabmatrix=veronica[1:50,],distance="jaccard")
  ppv <- prabclust(vei)
  veloci <- prabinit(prabmatrix=veronica[1:50,],rows.are.species=FALSE)
  velociclust <- prabclust(veloci,nnk=0)
  lociplots(ppv,velociclust$clustering,veloci,lcluster=3)