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PCA biplot

Source: R/PCA_plotfcns.R
pca_biplot.Rd

A scatter plot of the selected principal component scores overlaid with the corresponding principal component loadings.

Usage

pca_biplot(
  components = c(1, 2),
  points_to_label = "none",
  factor_name,
  scale_factor = 0.95,
  style = "points",
  label_features = FALSE,
  ...
)

Arguments

components

(numeric) The principal components used to generate the plot. The default is c(1, 2).

points_to_label

(character) points_to_label. Allowed values are limited to the following:

  • "none": No samples are labelled on the plot.

  • "all": All samples are labelled on the plot.

  • "outliers": Potential outliers are labelled on the plot.

The default is "none".

factor_name

(character) The name of a sample-meta column to use.

scale_factor

(numeric) The scaling factor applied to the loadings. The default is 0.95.

style

(character) Plot style. Allowed values are limited to the following:

  • "points": Loadings and scores are plotted as a scatter plot.

  • "arrows": The loadings are plotted as arrow vectors.

The default is "points".

label_features

(logical) Add feature labels. Allowed values are limited to the following:

  • "TRUE": Features are labelled.

  • "FALSE": Features are not labelled.

The default is FALSE.

...

Additional slots and values passed to struct_class.

Value

A pca_biplot object. This object has no output slots. See chart_plot in the struct package to plot this chart object.

Inheritance

A pca_biplot object inherits the following struct classes:

[pca_biplot] >> [chart] >> [struct_class]

Examples

M = pca_biplot(
      components = c(1, 2),
      points_to_label = "none",
      factor_name = "V1",
      scale_factor = 0.95,
      style = "points",
      label_features = FALSE)

C = pca_biplot(factor_name='Species')