% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/findMarkersTree.R
\name{plotMarkerDendro}
\alias{plotMarkerDendro}
\title{Plots dendrogram of \emph{findMarkersTree} output}
\usage{
plotMarkerDendro(
  tree,
  classLabel = NULL,
  addSensPrec = FALSE,
  maxFeaturePrint = 4,
  leafSize = 10,
  boxSize = 2,
  boxColor = "black"
)
}
\arguments{
\item{tree}{List object. The output of findMarkersTree()}

\item{classLabel}{A character value. The name of a specific label to draw
the path and rules. If NULL (default), the tree for all clusters is shown.}

\item{addSensPrec}{Logical. Print training sensitivities and precisions
for each cluster below leaf label? Default is FALSE.}

\item{maxFeaturePrint}{Numeric value. Maximum number of markers to print
at a given split. Default is 4.}

\item{leafSize}{Numeric value. Size of text below each leaf. Default is 24.}

\item{boxSize}{Numeric value. Size of rule labels. Default is 7.}

\item{boxColor}{Character value. Color of rule labels. Default is black.}
}
\value{
A ggplot2 object
}
\description{
Generates a dendrogram of the rules and performance
(optional) of the decision tree generated by findMarkersTree().
}
\examples{
\dontrun{
# Generate simulated single-cell dataset using celda
sim_counts <- celda::simulateCells("celda_CG", K = 4, L = 10, G = 100)

# Celda clustering into 5 clusters & 10 modules
cm <- celda_CG(sim_counts$counts, K = 5, L = 10, verbose = FALSE)

# Get features matrix and cluster assignments
factorized <- factorizeMatrix(sim_counts$counts, cm)
features <- factorized$proportions$cell
class <- celdaClusters(cm)

# Generate Decision Tree
DecTree <- findMarkersTree(features, class, threshold = 1)

# Plot dendrogram
plotMarkerDendro(DecTree)
}
}