HCtbl: Hierarchical clustering of spectral similarity data

In CluMSID: Clustering of MS2 Spectra for Metabolite Identification

Description

HCtbl() performs hierarchical clustering of spectral similarity data using average linkage as agglomeration criterion.

Usage

HCtbl(distmat, h = 0.95)

Arguments

distmat	A distance matrix as generated by distanceMatrix.
h	Height where the tree is to be cut, defaults to 0.95. See cutree for details.

Value

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

See Also

HCplot

Examples

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

my_HCtbl <- HCtbl(distmat[1:50,1:50], h = 0.8)

CluMSID documentation built on Nov. 8, 2020, 7:46 p.m.