gl.pcoa.plot: Bivariate or trivariate plot of the results of an ordination...

In dartR: Importing and Analysing 'SNP' and 'Silicodart' Data Generated by Genome-Wide Restriction Fragment Analysis

Bivariate or trivariate plot of the results of an ordination generated using gl.pcoa()

Description

This script takes output from the ordination generated by gl.pcoa() and plots the individuals classified by population.

Usage

gl.pcoa.plot(
  glPca,
  x,
  scale = FALSE,
  ellipse = FALSE,
  plevel = 0.95,
  pop.labels = "pop",
  interactive = FALSE,
  as.pop = NULL,
  hadjust = 1.5,
  vadjust = 1,
  xaxis = 1,
  yaxis = 2,
  zaxis = NULL,
  pt.size = 2,
  pt.colors = NULL,
  pt.shapes = NULL,
  label.size = 1,
  axis.label.size = 1.5,
  save2tmp = FALSE,
  verbose = NULL
)

Arguments

glPca	Name of the PCA or PCoA object containing the factor scores and eigenvalues [required].
x	Name of the genlight object or fd object containing the SNP genotypes or Tag P/A (SilicoDArT) genotypes or the Distance Matrix used to generate the ordination [required].
scale	If TRUE, scale the x and y axes in proportion to % variation explained [default FALSE].
ellipse	If TRUE, display ellipses to encapsulate points for each population [default FALSE].
plevel	Value of the percentile for the ellipse to encapsulate points for each population [default 0.95].
pop.labels	How labels will be added to the plot ['none'|'pop'|'legend', default = 'pop'].
interactive	If TRUE then the populations are plotted without labels, mouse-over to identify points [default FALSE].
as.pop	Assign another metric to represent populations for the plot [default NULL].
hadjust	Horizontal adjustment of label position in 2D plots [default 1.5].
vadjust	Vertical adjustment of label position in 2D plots [default 1].
xaxis	Identify the x axis from those available in the ordination (xaxis <= nfactors) [default 1].
yaxis	Identify the y axis from those available in the ordination (yaxis <= nfactors) [default 2].
zaxis	Identify the z axis from those available in the ordination for a 3D plot (zaxis <= nfactors) [default NULL].
pt.size	Specify the size of the displayed points [default 2].
pt.colors	Optionally provide a vector of nPop colors (run gl.select.colors() for color options) [default NULL].
pt.shapes	Optionally provide a vector of nPop shapes (run gl.select.shapes() for shape options) [default NULL].
label.size	Specify the size of the point labels [default 1].
axis.label.size	Specify the size of the displayed axis labels [default 1.5].
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].

Details

The factor scores are taken from the output of gl.pcoa() and the population assignments are taken from from the original data file. In the bivariate plots, the specimens are shown optionally with adjacent labels and enclosing ellipses. Population labels on the plot are shuffled so as not to overlap (using package {directlabels}). This can be a bit clunky, as the labels may be some distance from the points to which they refer, but it provides the opportunity for moving labels around using graphics software (e.g. Adobe Illustrator).

3D plotting is activated by specifying a zaxis.

Any pair or trio of axes can be specified from the ordination, provided they are within the range of the nfactors value provided to gl.pcoa(). In the 2D plots, axes can be scaled to represent the proportion of variation explained. In any case, the proportion of variation explained by each axis is provided in the axis label.

Colors and shapes of the points can be altered by passing a vector of shapes and/or a vector of colors. These vectors can be created with gl.select.shapes() and gl.select.colors() and passed to this script using the pt.shapes and pt.colors parameters.

Points displayed in the ordination can be identified if the option interactive=TRUE is chosen, in which case the resultant plot is ggplotly() friendly. Identification of points is by moving the mouse over them. Refer to the plotly package for further information. The interactive option is automatically enabled for 3D plotting.

Value

returns no value (i.e. NULL)

Author(s)

Custodian: Arthur Georges – Post to https://groups.google.com/d/forum/dartr

See Also

gl.pcoa

Other Exploration/visualisation functions: gl.select.colors(), gl.select.shapes(), gl.smearplot()

Examples

# SET UP DATASET
gl <- testset.gl
levels(pop(gl))<-c(rep('Coast',5),rep('Cooper',3),rep('Coast',5),
rep('MDB',8),rep('Coast',7),'Em.subglobosa','Em.victoriae')
# RUN PCA
pca<-gl.pcoa(gl,nfactors=5)
# VARIOUS EXAMPLES
gl.pcoa.plot(pca, gl, ellipse=TRUE, plevel=0.95, pop.labels='pop', 
axis.label.size=1, hadjust=1.5,vadjust=1)
gl.pcoa.plot(pca, gl, ellipse=TRUE, plevel=0.99, pop.labels='legend', 
axis.label.size=1)
gl.pcoa.plot(pca, gl, ellipse=TRUE, plevel=0.99, pop.labels='legend', 
axis.label.size=1.5,scale=TRUE)
gl.pcoa.plot(pca, gl, ellipse=TRUE, axis.label.size=1.2, xaxis=1, yaxis=3, 
scale=TRUE)
gl.pcoa.plot(pca, gl, pop.labels='none',scale=TRUE)
gl.pcoa.plot(pca, gl, axis.label.size=1.2, interactive=TRUE)
gl.pcoa.plot(pca, gl, ellipse=TRUE, plevel=0.99, xaxis=1, yaxis=2, zaxis=3)
# color AND SHAPE ADJUSTMENTS
shp <- gl.select.shapes(select=c(16,17,17,0,2))
col <- gl.select.colors(library='brewer',palette='Spectral',ncolors=11,
select=c(1,9,3,11,11))
gl.pcoa.plot(pca, gl, ellipse=TRUE, plevel=0.95, pop.labels='pop', 
pt.colors=col, pt.shapes=shp, axis.label.size=1, hadjust=1.5,vadjust=1)
gl.pcoa.plot(pca, gl, ellipse=TRUE, plevel=0.99, pop.labels='legend',
 pt.colors=col, pt.shapes=shp, axis.label.size=1)
 
 test <- gl.pcoa(platypus.gl)
 gl.pcoa.plot(glPca = test, x = platypus.gl)

dartR documentation built on June 8, 2023, 6:48 a.m.