| gl.dist.pop | R Documentation |
This script calculates various distances between populations based on allele frequencies (SNP genotypes) or frequency of presences in presence-absence data (Euclidean and Fixed-diff distances only).
gl.dist.pop( x, method = "euclidean", plot.out = TRUE, scale = FALSE, output = "dist", plot_theme = theme_dartR(), plot_colors = two_colors, save2tmp = FALSE, verbose = NULL )
x |
Name of the genlight containing the SNP genotypes [required]. |
method |
Specify distance measure [default euclidean]. |
plot.out |
If TRUE, display a histogram of the genetic distances, and a whisker plot [default TRUE]. |
scale |
If TRUE and method='Euclidean', the distance will be scaled to fall in the range [0,1] [default FALSE]. |
output |
Specify the format and class of the object to be returned, dist for a object of class dist, matrix for an object of class matrix [default "dist"]. |
plot_theme |
User specified theme [default theme_dartR()]. |
plot_colors |
Vector with two color names for the borders and fill [default two_colors]. |
save2tmp |
If TRUE, saves any ggplots and listings to the session temporary directory (tempdir) [default FALSE]. |
verbose |
Verbosity: 0, silent or fatal errors; 1, begin and end; 2, progress log ; 3, progress and results summary; 5, full report [default 2 or as specified using gl.set.verbosity]. |
The distance measure can be one of 'euclidean', 'fixed-diff', 'reynolds', 'nei' and 'chord'. Refer to the documentation of functions described in the the dartR Distance Analysis tutorial for algorithms and definitions.
An object of class 'dist' giving distances between populations
author(s): Arthur Georges. Custodian: Arthur Georges – Post to https://groups.google.com/d/forum/dartr
## Not run: # SNP genotypes D <- gl.dist.pop(possums.gl[1:90,1:100], method='euclidean') D <- gl.dist.pop(possums.gl[1:90,1:100], method='euclidean',scale=TRUE) #D <- gl.dist.pop(possums.gl, method='nei') #D <- gl.dist.pop(possums.gl, method='reynolds') #D <- gl.dist.pop(possums.gl, method='chord') #D <- gl.dist.pop(possums.gl, method='fixed-diff') #Presence-Absence data [only 10 individuals due to speed] D <- gl.dist.pop(testset.gs[1:10,], method='euclidean') ## End(Not run) res <- gl.dist.pop(platypus.gl)