OPTICStbl: Density-based clustering of spectral similarity data

In tdepke/CluMSID: Clustering of MS2 Spectra for Metabolite Identification

Density-based clustering of spectral similarity data

Description

OPTICStbl() performs density-based clustering of spectral similarity data using the OPTICS algorithm.

Usage

OPTICStbl(distmat, eps = 10000, minPts = 3, eps_cl = 0.5)

Arguments

distmat	A distance matrix as generated by distanceMatrix.
eps, minPts	OPTICS parameters, see optics.
eps_cl	The reachability distance used for cluster determination, see extractDBSCAN.

Details

The function internally uses optics and extractDBSCAN from the dbscan package.

Value

A data.frame with feature name, cluster ID and OPTICS order for each feature in distmat.

See Also

OPTICSplot

Examples

load(file = system.file("extdata",
    "distmat.RData",
    package = "CluMSIDdata"))

my_OTPICStbl <- OPTICStbl(distmat[1:50,1:50], eps_cl = 0.7)

tdepke/CluMSID documentation built on April 10, 2022, noon