autoplot_gt_dapc: Autoplots for 'gt_dapc' objects

In tidypopgen: Tidy Population Genetics

Autoplots for gt_dapc objects

Description

For gt_dapc, the following types of plots are available:

• screeplot: a plot of the eigenvalues of the discriminant axes

• scores a scatterplot of the scores of each individual on two discriminant axes (defined by ld)

• loadings a plot of loadings of all loci for a discriminant axis (chosen with ld)

• components a bar plot showing the probability of assignment to each cluster

Usage

## S3 method for class 'gt_dapc'
autoplot(
  object,
  type = c("screeplot", "scores", "loadings", "components"),
  ld = NULL,
  group = NULL,
  n_col = 1,
  ...
)

Arguments

object	an object of class gt_dapc
type	the type of plot (one of "screeplot", "scores", "loadings", and "components")
ld	the principal components to be plotted: for scores, a pair of values e.g. c(1,2); for loadings either one or more values.
group	a vector of group memberships to order the individuals in "components" plot. If NULL, the clusters used for the DAPC will be used.
n_col	for loadings plots, if multiple LD axis are plotted, how many columns should be used.
...	not currently used.

Details

autoplot produces simple plots to quickly inspect an object. They are not customisable; we recommend that you use ggplot2 to produce publication ready plots.

Value

a ggplot2 object

Examples

# Create a gen_tibble of lobster genotypes
bed_file <-
  system.file("extdata", "lobster", "lobster.bed", package = "tidypopgen")
lobsters <- gen_tibble(bed_file,
  backingfile = tempfile("lobsters"),
  quiet = TRUE
)

# Remove monomorphic loci and impute
lobsters <- lobsters %>% select_loci_if(loci_maf(genotypes) > 0)
lobsters <- gt_impute_simple(lobsters, method = "mode")

# Create PCA and run DAPC
pca <- gt_pca_partialSVD(lobsters)
populations <- as.factor(lobsters$population)
dapc_res <- gt_dapc(pca, n_pca = 6, n_da = 2, pop = populations)

# Screeplot
autoplot(dapc_res, type = "screeplot")

# Scores plot
autoplot(dapc_res, type = "scores", ld = c(1, 2))

# Loadings plot
autoplot(dapc_res, type = "loadings", ld = 1)

# Components plot
autoplot(dapc_res, type = "components", group = populations)

tidypopgen documentation built on Aug. 28, 2025, 1:08 a.m.