Plot Seurat embedding with cluster confusion links — PlotConfusionLinks • scClustEval

Visualize clustering confusion on Seurat UMAP/t-SNE embedding

Usage

PlotConfusionLinks(
  object,
  result,
  reduction = "umap",
  cluster_col = NULL,
  matrix_type = "R1",
  threshold = 0.1,
  line_color = "#ffa500",
  line_scale = 10,
  point_size = 0.5,
  title = NULL,
  show_legend = TRUE
)

Arguments

object: Seurat object
result: scClustEval assessment result
reduction: Name of reduction to plot (default: "umap")
cluster_col: Cluster column to use (default: uses result info or Idents)
matrix_type: Which confusion matrix to use: "R1" or "R2"
threshold: Threshold for drawing lines (default: 0.1)
line_color: Color for connection lines
line_scale: Scale factor for line widths
point_size: Size of cell points
title: Plot title
show_legend: Show cluster legend

Value

A ggplot2 object

Details

This function creates a UMAP/t-SNE plot showing cells colored by cluster, with lines connecting cluster centroids based on confusion matrix values. This helps identify which clusters are transcriptionally similar.

Examples

if (FALSE) { # \dontrun{
# Run assessment
result <- RunAssessment(seurat_obj)

# Plot UMAP with confusion links
PlotConfusionLinks(seurat_obj, result, threshold = 0.1)

# Use t-SNE instead
PlotConfusionLinks(seurat_obj, result, reduction = "tsne")
} # }