% 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)
 }

 }