specmine (version 3.1.6)

pca_kmeans_plot2D: 2D PCA k-means plot

Description

Groups the points with the clusters given by k-means in a 2D PCA scores plot.

Usage

pca_kmeans_plot2D(dataset, pca.result, num.clusters = 3, 
pcas = c(1, 2), kmeans.result = NULL, labels = FALSE, bw=FALSE,
ellipses = FALSE, leg.pos = "right", xlim = NULL, ylim = NULL)

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.

ellipses

boolean value that indicates if an ellipse will be drawn on each group of the metadata's variable. Ellipses will not be drawn if bw=TRUE.

bw

if TRUE, it will be displayed a black and white plot. It defaults to FALSE.

leg.pos

legend position.

xlim

vector with two positions with the x-axis limits.

ylim

vector with two positions with the y-axis limits.

Examples

# NOT RUN {
  ## Example of a 2D PCA k-means plot
  library(specmine.datasets)
  data(cachexia)
  pca.result = pca_analysis_dataset(cachexia)
  pca_kmeans_plot2D(cachexia, pca.result, num.clusters = 3, pcas = c(1,2))
# }