hdbscan: Conveinience function to perform HDBSCAN via reticulate.

In jenzopr/singlecellutils: Utility functions for single-cell data

Description

Performs HDBSCAN clustering on a SingleCellExperiment object. The algorithm is explained in detail in McInnes et. al. and needs the python package hdbscan installed.

Usage

hdbscan(object, use_dimred, min_samples = 7L, min_cluster_size = 9L,
  outlier = 0, seed = NULL)

Arguments

object	A SingleCellExperiment object.
use_dimred	A string or integer scalar indicating the reduced dimension result in reducedDims(object) to use as input.
min_samples	Measure of how conservative the clustering should to be. The larger the value of min_samples, the more conservative the clustering and more points will be declared as noise, and clusters will be restricted to progressively more dense areas.
min_cluster_size	The smallest size grouping that is considered a cluster.
outlier	Determines how outliers are encoded in the resulting clustering.
seed	A numeric seed to initialize the random number generator.

Value

A factor with the assigned cluster.

jenzopr/singlecellutils documentation built on June 12, 2019, 2:51 a.m.