This function applies HDBSCAN, a density-based clustering algorithm, to the corrected dimension reduction of a Seurat object.
hdbscan.seurat(
seu,
batch.var = "Batch",
reduction = "pca",
dims = seq_len(15),
minPts = 25
)A Seurat object with two additional columns in its meta.data:
dbscan_cluster and initial_cluster.
A Seurat object containing integrated or batch-corrected data (e.g. PCA results).
Character string specifying the metadata column that contains batch information. Default is "Batch".
Character string specifying the name of the dimension reduction to use (e.g. "PCA"). Default is "PCA".
Numeric vector indicating the dimensions to be used for initial clustering. Default is 1:15.
Integer specifying the minimum number of points required to form a cluster.
This value is passed to the hdbscan function. Default is 25.
getIDEr, estimateProb