plot.locus.dist: Plot a phylogeny with a graphical representation of locus...
In RADami: Phylogenetic Analysis of RADseq Data

Description Usage Arguments Details Value Author(s) See Also Examples

Plots a phylogeny lined up with the locus-sharing similarity matrix in graphical style

## S3 method for class 'locus.dist'
plot(x, tr, trW = 3, plotW = 5, labelsW = 3, plotGap = 0.25,
     scalar = 1.5, barH = 1, barW = 10, bar.cex = 0.5,
		 point.pch = c(21, 21),
     cols = c('black', 'red'), ...)

`x`	output from `locus.dist`
`tr`	an object of class `phylo` with tips named the same as the rows of `locD`
`trW`	width of the panels holding the tree
`plotW`	width of the panel holding the matrix plot
`labelsW`	width of the panel holding the taxon labels (right side of plot)
`plotGap`	gap between the side panels and the central panel
`scalar`	the scalar for the dots in the locus distance plot
`barH`	height of the panel holding the bars
`barW`	width of individual bars; goes to `lwd`
`bar.cex`	font size for numbers above the bars
`point.pch`	plot character (`pch`) for the off-diagonal and diagonal elements of the matrix plot
`cols`	color for the off-diagonal and diagonal elements of the matrix plot
`...`	additional arguments passed along to `text`

Use default options in locus.dist to get a sensible plot. Also, while different plotting characters can be defined for the off-diagonal and diagonal elements of the matrix plot, these may be hard to compare with each other in size; probably the diagonal elements are better distinguished by color or shading.

Currently, this function is implemented using layout, which makes it rather clunky and inflexible.

A list comprising:

`Xs`	the x-coordinates of dots in the matrix plot
`heights`	heights of the bars at the top of the plot, which show the overlap of each individual averaged over all other individuals on the plot

Andrew Hipp

plot.rankedPartitionedRAD, locus.dist

  data(oak.rads)
  data(oak.tree)
  plot.locus.dist(locus.dist(oak.rads, proportional = TRUE), oak.tree)
  # and now a nicer-looking plot:
  plot.locus.dist(locus.dist(oak.rads, proportional = TRUE, upper = TRUE),
                  ladderize(oak.tree), trW = 1, labelsW = 1, scalar = 3)