poppr (version 1.1.1)

plot_poppr_msn: Plot minimum spanning networks produced in poppr.

Description

This function allows you to take the output of poppr.msn and bruvo.msn and customize the plot by labeling groups of individuals, size of nodes, and adjusting the palette and scale bar.

Usage

plot_poppr_msn(x, poppr_msn, gscale = TRUE, gadj = 3, glim = c(0, 0.8),
  gweight = 1, wscale = TRUE, inds = "ALL", quantiles = TRUE,
  nodelab = 2, cutoff = NULL, palette = NULL, layfun = layout.auto,
  beforecut = FALSE, ...)

Arguments

x

a genind or genclone object from which poppr_msn was derived.

poppr_msn

a list produced from either poppr.msn or bruvo.msn. This list should contain a graph, a vector of population names and a vector of hexad

inds

a character vector indicating which individual names to label nodes with. See details.

quantiles

logical. When set to TRUE (default), the scale bar will be composed of the quantiles from the observed edge weights. When set to FALSE, the scale bar will be composed of a smooth gradient from the minimum edge

nodelab

an integer specifying the smallest size of node to label. See details.

cutoff

a number indicating the longest distance to display in your graph. This is performed by removing edges with weights greater than this number.

palette

a function or character corresponding to a specific palette you want to use to delimit your populations. The default is whatever palette was used to produce the original graph.

layfun

a function specifying the layout of nodes in your graph. It defaults to layout.auto.

beforecut

if TRUE, the layout of the graph will be computed before any edges are removed with cutoff. If FALSE (Default), the layout will be computed after any edges are removed.

...

any other parameters to be passed on to plot.igraph.

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.

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).

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 nodes.

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

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.

Details

The previous incarnation of msn plotting in poppr simply plotted the minimum spanning network with the legend of populations, but did not provide a scale bar and it did not provide the user a simple way of manipulating the layout or labels. This function allows the user to manipulate many facets of graph creation, making the creation of minimum spanning networks ever so slightly more user friendly. Note that this function will only plot individual names, not MLG names since the naming convention for those are arbitrary.

This function must have both the source data and the output msn to work. The source data must contain the same population structure as the graph. Every other parameter has a default setting.

Parameter details{

• indsThis will take in the name of a query individual in your data set and will use that to query any other individuals that share multilocus genotypes and label their node on the graph. The default is to label all the nodes, but you can set it to a name that doesn't exist to label none of the nodes.
• nodelabIf a node is not labeled by individual, this will label the size of the nodes greater than or equal to this value. If you don't want to label the size of the nodes, simply set this to a very high number.
• cutoffThis is useful for when you want to investigate groups of multilocus genotypes separated by a specific distance or if you have two distinct populations and you want to physically separate them in your network.
• beforecutThis is an indicator useful if you want to maintain the same position of the nodes before and after removing edges with thecutoffargument. This works best if you set a seed before you run the function.

}

See Also

layout.auto plot.igraph poppr.msn bruvo.msn greycurve delete.edges palette

Examples

# Using a data set of the Aphanomyces eutieches root rot pathogen.
data(Aeut)
adist <- diss.dist(Aeut, percent = TRUE)
amsn <- poppr.msn(Aeut, adist, showplot = FALSE)

# Default
library(igraph) # To get all the layouts.
set.seed(500)
plot_poppr_msn(Aeut, amsn, gadj = 15, beforecut = TRUE)

# Removing link between populations and labelling no individuals
set.seed(500)
plot_poppr_msn(Aeut, amsn, inds = "none", gadj = 15, beforecut = TRUE, cutoff = 0.2)

# Labelling individual #57 because it is an MLG that crosses popualtions
# Showing clusters of MLGS with at most 5\% variation
# Notice that the Mt. Vernon population appears to be more clonal
set.seed(50)
plot_poppr_msn(Aeut, amsn, gadj = 15, cutoff = 0.05, inds = "57")


data(partial_clone)
pcmsn <- bruvo.msn(partial_clone, replen = rep(1, 10))
plot_poppr_msn(partial_clone, pcmsn, palette = rainbow, inds = "sim 20")

# Something pretty
data(microbov)
mdist <- diss.dist(microbov, percent = TRUE)
micmsn <- poppr.msn(microbov, mdist, showplot = FALSE)

plot_poppr_msn(microbov, micmsn, palette = "terrain.colors", inds = "n",
  quantiles = FALSE)
plot_poppr_msn(microbov, micmsn, palette = "terrain.colors", inds = "n",
  cutoff = 0.3, quantiles = FALSE)