pca_biplot: PCA biplot

In structToolbox: Data processing & analysis tools for Metabolomics and other omics

Description

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.

Examples

C = pca_biplot(factor_name='Species')

structToolbox documentation built on Nov. 8, 2020, 6:54 p.m.