plsda_scores_plot: PLSDA scores plot

Description Usage Arguments Details Value References Examples

View source: R/PLSDA_charts.R

Description

A scatter plot of the selected PLSDA scores.

Usage

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plsda_scores_plot(
  components = c(1, 2),
  points_to_label = "none",
  factor_name,
  ...
)

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.

...

Additional slots and values passed to struct_class.

Details

This object makes use of functionality from the following packages:

Value

A plsda_scores_plot object.

References

Mevik B, Wehrens R, Liland K (2020). pls: Partial Least Squares and Principal Component Regression. R package version 2.7-3, https://CRAN.R-project.org/package=pls.

Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org.

Examples

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D = iris_DatasetExperiment()
M = mean_centre()+PLSDA(factor_name='Species')
M = model_apply(M,D)

C = plsda_scores_plot(factor_name='Species')
chart_plot(C,M[2])

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