pca_scoresplot2D: PCA 2D scores plot

In specmine: Metabolomics and Spectral Data Analysis and Mining

PCA 2D scores plot

Description

Creates a 2D PCA scores plot.

Usage

pca_scoresplot2D(
  dataset,
  pca.result,
  column.class = NULL,
  pcas = c(1, 2),
  labels = FALSE,
  ellipses = FALSE,
  bw = FALSE,
  pallette = 2,
  leg.pos = "right",
  xlim = NULL,
  ylim = NULL
)

Arguments

dataset	Dataset used in the PCA.
pca.result	PCA result object.
column.class	Optional metadata column used for colouring groups.
pcas	Principal components to plot.
labels	Logical indicating whether sample labels should be shown.
ellipses	Logical indicating whether group ellipses should be drawn.
bw	Logical indicating whether a black-and-white style should be used.
pallette	Brewer palette identifier.
leg.pos	Legend position.
xlim	Optional x-axis limits.
ylim	Optional y-axis limits.

Value

A ggplot object.

Examples

datamat <- matrix(
  rnorm(20),
  nrow = 4,
  dimnames = list(paste0("x", 1:4), paste0("s", 1:5))
)
metadata <- data.frame(class = factor(c("A", "A", "B", "B", "A")))
dataset <- list(data = datamat, metadata = metadata)
pca_res <- pca_analysis_dataset(dataset)
pca_scoresplot2D(dataset, pca_res, column.class = "class")

specmine documentation built on Aug. 5, 2026, 5:06 p.m.