This function applies HDBSCAN, a density-based clustering method, on the corrected dimension reduction.
Usage
hdbscan.seurat(seu, reduction = "pca", dims = seq_len(15), minPts = 25)Arguments
- seu
a Seurat object containing integrated or batch corrected PCA.
- reduction
Character. Name of the dimension reduction after integration or batch correction. (Default: PCA)
- dims
Numeric vector. Dimensions used for initial clustering. (Default: 1:15)
- minPts
Interger. Minimum size of clusters. Will be passed to the `hdbscan` function. (Default: 25)
Value
A Seurat object having two additional columns in its meta.data: dbscan_cluster and initial_cluster.
See also
Usage of this function should be followed by
getIDEr and estimateProb.