pca_scores_plot {structToolbox} | R Documentation |
Plots a 2d scatter plot of the selected components
pca_scores_plot( components = c(1, 2), points_to_label = "none", factor_name, ellipse = "all", ellipse_type = "norm", ellipse_confidence = 0.95, label_filter = character(0), label_factor = "rownames", label_size = 3.88, ... )
components |
(numeric) The components selected for plotting. The default is |
points_to_label |
(character) Points to label. Allowed values are limited to the following:
The default is |
factor_name |
(character) The name of a sample-meta column to use. |
ellipse |
(character) Plot ellipses. Allowed values are limited to the following:
The default is |
ellipse_type |
(character) Type of ellipse. Allowed values are limited to the following:
The default is |
ellipse_confidence |
(numeric) The confidence level for plotting ellipses. The default is |
label_filter |
(character) Labels are only plotted for the named groups. If zero-length then all groups are included. The default is |
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 |
label_size |
(numeric) The text size of labels. Note this is not in Font Units. The default is |
... |
Additional slots and values passed to |
A
pca_scores_plot
object. This object has no output
slots.
See chart_plot
in the struct
package to plot this chart object.
D = iris_DatasetExperiment() M = mean_centre() + PCA() M = model_apply(M,D) C = pca_scores_plot(factor_name = 'Species') chart_plot(C,M[2])