HDBSCAN.Seurat: Hierarchical Density-Based Spatial Clustering of Applications...
In dbrookeUAB/dbsinglecell: Dewey Brooke's Single-Cell Toolkit

HDBSCAN.Seurat

R Documentation

Hierarchical Density-Based Spatial Clustering of Applications with Noise

Description

Hierarchical Density-Based Spatial Clustering of Applications with Noise

Usage

## S3 method for class 'Seurat'
HDBSCAN(
  object,
  reduction = "umap",
  dims = NULL,
  algorithm = "best",
  alpha = 1,
  prediction_data = TRUE,
  approx_min_span_tree = TRUE,
  gen_min_span_tree = FALSE,
  leaf_size = 30,
  metric = "euclidean",
  min_cluster_size = 1000L,
  min_samples = 1L,
  cluster_selection_epsilon = 0.1,
  cluster_selection_method = "leaf",
  nThreads = parallel::detectCores() - 1,
  return_seurat = TRUE,
  return_full = FALSE
)

Arguments

`prediction_data`	not sure what this is for. Will update later.
`return_seurat`	logical to return the result within the orignal object or as the raw HDBSCAN result