pca_scores_plot {structToolbox} | R Documentation

## PCA scores plot

### Description

Plots a 2d scatter plot of the selected components

### Usage

    pca_scores_plot(
      components = c(1, 2),
      points_to_label = "none",
      factor_name,
      ellipse = "all",
      label_filter = character(0),
      label_factor = "rownames",
      label_size = 3.88,
      ...
    )

### Arguments

`components` | (numeric) The components selected for plotting. The default is `c(1, 2)`.
`points_to_label` | (character) Points to label. Allowed values are limited to the following: `"none"`: No samples labels are displayed. `"all"`: The labels for all samples are displayed. `"outliers"`: Labels for for potential outlier samples are displayed. The default is `"none"`.
`factor_name` | (character) The name of a sample-meta column to use.
`ellipse` | (character) Plot ellipses. Allowed values are limited to the following: `"all"`: Hotelling T2 95% ellipses are plotted for all groups and all samples. `"group"`: Hotelling T2 95% ellipses are plotted for all groups. `"none"`: Ellipses are not included on the plot. `"sample"`: A Hotelling T2 95% ellipse is plotted for all samples (ignoring group). The default is `"all"`.
`label_filter` | (character) Labels are only plotted for the named groups. If zero-length then all groups are included. The default is `character(0)`.
`label_factor` | (character) The column name of sample_meta to use for labelling samples on the plot. "rownames" will use the row names from sample_meta. The default is `"rownames"`.
`label_size` | (numeric) The text size of labels. Note this is not in Font Units. The default is `3.88`.
`...` | Additional slots and values passed to `struct_class`.

### Value

A `pca_scores_plot` object.

### Examples

    D = iris_DatasetExperiment()
    M = mean_centre() + PCA()
    M = model_apply(M,D)
    C = pca_scores_plot(factor_name = 'Species')
    chart_plot(C,M[2])

[Package structToolbox version 1.2.0 Index]