poppr (version 1.1.1)

poppr.msn: Create a minimum spanning network of selected populations using a distance matrix.

Description

Create a minimum spanning network of selected populations using a distance matrix.

Usage

poppr.msn(pop, distmat, palette = topo.colors, sublist = "All",
  blacklist = NULL, vertex.label = "MLG", gscale = TRUE, glim = c(0,
  0.8), gadj = 3, gweight = 1, wscale = TRUE, showplot = TRUE, ...)

Arguments

pop

a genind object

distmat

a distance matrix that has been derived from your data set.

palette

a function defining the color palette to be used to color the populations on the graph. It defaults to topo.colors, but you can easily create new schemes by using

sublist

a vector of population names or indexes that the user wishes to keep. Default to "ALL".

blacklist

a vector of population names or indexes that the user wishes to discard. Default to NULL

vertex.label

a vector of characters to label each vertex. There are two defaults: "MLG" will label the nodes with the multilocus genotype from the original data set and "inds" will label the nodes with the representative in

gscale

"grey scale". If this is TRUE, this will scale the color of the edges proportional to the observed distance, with the lines becoming darker for more related nodes. See greycurve for detai

glim

"grey limit". Two numbers between zero and one. They determine the upper and lower limits for the gray function. Default is 0 (black) and 0.8 (20% black). See greycu

gadj

"grey adjust". a positive integer greater than zero that will serve as the exponent to the edge weight to scale the grey value to represent that weight. See greycurve for details.

gweight

"grey weight". an integer. If it's 1, the grey scale will be weighted to emphasize the differences between closely related nodes. If it is 2, the grey scale will be weighted to emphasize the differences between more distantly related no

wscale

"width scale". If this is TRUE, the edge widths will be scaled proportional to the inverse of the observed distance , with the lines becoming thicker for more related nodes.

showplot

logical. If TRUE, the graph will be plotted. If FALSE, it will simply be returned.

...

any other arguments that could go into plot.igraph

Value

• graph
  a minimum spanning network with nodes corresponding to MLGs within the data set. Colors of the nodes represent population membership. Width and color of the edges represent distance.
• populations
  a vector of the population names corresponding to the vertex colors
• colors
  a vector of the hexadecimal representations of the colors used in the vertex colors

See Also

nancycats, upgma, nj, nodelabels, na.replace, missingno, bruvo.msn, greycurve.

Examples

# Load the data set and calculate the distance matrix for all individuals.
data(Aeut)
A.dist <- diss.dist(Aeut)

# Graph it.
A.msn <- poppr.msn(Aeut, A.dist, gadj=15, vertex.label=NA)

# Set subpopulation structure.
Aeut.sub <- splitcombine(Aeut, method=2, hier=c("Pop", "Subpop"))

# Plot respective to the subpopulation structure
As.msn <- poppr.msn(Aeut.sub, A.dist, gadj=15, vertex.label=NA)

# Show only the structure of the Athena population.
As.msn <- poppr.msn(Aeut.sub, A.dist, gadj=15, vertex.label=NA, sublist=1:10)

# Let's look at the structure of the microbov data set
data(microbov)
micro.dist <- diss.dist(microbov)
micro.msn <- poppr.msn(microbov, diss.dist(microbov), vertex.label=NA)

Let's plot it and show where individuals have < 15% of their genotypes
different.

plot.igraph(micro.msn$graph, edge.label = ifelse(E(micro.msn$graph)$weight < 0.15,
round(E(micro.msn$graph)$weight, 3), NA), vertex.size=2, edge.label.color="red")