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specmine (version 3.0.1)

pca_kmeans_plot3D: 3D PCA k-means plot (interactive)

Description

Groups the points with the clusters given by k-means in a interactive 3D PCA scores plot.

Usage

pca_kmeans_plot3D(dataset, pca.result, num.clusters = 3, 
pcas = c(1, 2, 3), kmeans.result = NULL, labels = FALSE, 
size = 1, ...)

Arguments

dataset

list representing the dataset from a metabolomics experiment.

pca.result

prcomp object with the PCA results.

num.clusters

number of clusters of k-means.

pcas

vector with the principal components to be plotted.

kmeans.result

result from k-means. If null k-means is performed in the function.

labels

boolean value indicating if the samples' labels will be shown.

size

parameter of plot3d from rgl package.

…

additional parameters of plot3d function from rgl package.

Examples

Run this code
# NOT RUN {
  ### Example of a 3D PCA k-means plot
  pca.result = pca_analysis_dataset(cachexia)
  pca_kmeans_plot3D(cachexia, pca.result, num.clusters = 3, 
    		    pcas = c(1,2,3))
  
# }

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