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Autoplots for gt_dapc objects

Source: R/autoplot_gt_dapc.R
autoplot_gt_dapc.Rd

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.

Value

a ggplot2 object

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.

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)
#> Warning: Ignoring unknown parameters: `size`