pca_biplot {structToolbox} | R Documentation

## PCA biplot

### 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')

[Package structToolbox version 1.2.0 Index]