hdbscan.seurat {CIDER}R Documentation

Initial clustering for evaluating integration

Description

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.


[Package CIDER version 0.99.0 Index]