% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/PCA_plotfcns.R
\name{pca_biplot}
\alias{pca_biplot}
\title{PCA biplot}
\usage{
pca_biplot(
  components = c(1, 2),
  points_to_label = "none",
  factor_name,
  scale_factor = 0.95,
  style = "points",
  label_features = FALSE,
  ...
)
}
\arguments{
\item{components}{(numeric) The principal components used to generate the plot. The default is \code{c(1, 2)}.}

\item{points_to_label}{(character) points_to_label. Allowed values are limited to the following: \itemize{ \item{\code{"none"}: No samples are labelled on the plot.}\item{\code{"all"}: All samples are labelled on the plot.}\item{\code{"outliers"}: Potential outliers are labelled on the plot.}} The default is \code{"none"}.}

\item{factor_name}{(character) The name of a sample-meta column to use.}

\item{scale_factor}{(numeric) The scaling factor applied to the loadings. The default is \code{0.95}.\cr}

\item{style}{(character) Plot style. Allowed values are limited to the following: \itemize{ \item{\code{"points"}: Loadings and scores are plotted as a scatter plot.}\item{\code{"arrows"}: The loadings are plotted as arrow vectors.}} The default is \code{"points"}.}

\item{label_features}{(logical) Add feature labels. Allowed values are limited to the following: \itemize{ \item{\code{"TRUE"}: Features are labelled.}\item{\code{"FALSE"}: Features are not labelled.}} The default is \code{FALSE}.\cr}

\item{...}{Additional slots and values passed to \code{struct_class}.}
}
\value{
A  \code{
pca_biplot
} object. This object has no \code{output} slots.
See \code{\link[struct]{chart_plot}} in the \code{struct} package to plot this chart object.
}
\description{
A scatter plot of the selected principal component scores overlaid with the corresponding principal component loadings.
}
\section{Inheritance}{

A \code{pca_biplot} object inherits the following \code{struct} classes: \cr\cr
\verb{[pca_biplot]} >> \verb{[chart]} >> \verb{[struct_class]}
}

\examples{
M = pca_biplot(
      components = c(1, 2),
      points_to_label = "none",
      factor_name = "V1",
      scale_factor = 0.95,
      style = "points",
      label_features = FALSE)

C = pca_biplot(factor_name='Species')
}