dataSNN: Generate cell clusters using hierarchical clustering and...

In linquynus/RCAv2-beta: Reference Component Analysis

Description

Generate cell clusters using hierarchical clustering and dynamic tree cutting.

Usage

dataSNN(rca.obj, k = 10, eps = 8, minPts = 5, dist.fun = "All")

Arguments

rca.obj	RCA object.
k	Number of cells to consider in the neirest neighbour graph. Default is 10.
eps	Number of cells that have to be similar to connect 2 cells in a network. Default is 8
minPts	Number of cells with at least eps neighbours to be considered a core point. Default is 5.
dist.fun	Either PCA or All. For PCA, a PCA reduction of the projection will be performed before the correlation matrix is computed.

Value

RCA object.

linquynus/RCAv2-beta documentation built on Aug. 9, 2020, 12:34 a.m.