DBClustDimension: Perform spectral density clustering on single cells

In nukappa/seurat_v2: Seurat : R toolkit for single cell genomics

Description

Find point clounds single cells in a two-dimensional space using density clustering (DBSCAN).

Usage

DBClustDimension(object, dim.1 = 1, dim.2 = 2, reduction.use = "tsne",
  G.use = NULL, set.ident = TRUE, seed.use = 1, ...)

Arguments

object	Seurat object
dim.1	First dimension to use
dim.2	second dimension to use
reduction.use	Which dimensional reduction to use (either 'pca' or 'ica')
G.use	Parameter for the density clustering. Lower value to get more fine-scale clustering
set.ident	TRUE by default. Set identity class to the results of the density clustering. Unassigned cells (cells that cannot be assigned a cluster) are placed in cluster 1, if there are any.
seed.use	Random seed for the dbscan function
...	Additional arguments to be passed to the dbscan function

nukappa/seurat_v2 documentation built on May 24, 2019, 9:57 a.m.