copheneticCorrelation: Cophenetic correlation coefficient

In acabassi/klic: Kernel Learning Integrative Clustering

Description

Compute the cophenetic correlation coefficient of a kernel matrix, which is a measure of how faithfully hierarchical clustering would preserve the pairwise distances between the original data points.

Usage

copheneticCorrelation(kernelMatrix)

Arguments

kernelMatrix

kernel matrix.

Value

This functions returns the cophenetic correlation coefficient of the kernel matrix provided as input.

Author(s)

Alessandra Cabassi [e-mail]

References

Cabassi, A. and Kirk, P. D. W. (2019). Multiple kernel learning for integrative consensus clustering of genomic datasets. arXiv preprint. arXiv:1904.07701.

Sokal, R.R. and Rohlf, F.J., 1962. The comparison of dendrograms by objective methods. Taxon, 11(2), pp.33-40.

Examples

# Load kernel matrix
consensus_matrix <- as.matrix(read.csv(system.file('extdata',
'consensus_matrix1.csv', package = 'klic'), row.names = 1))

# Compute cophenetic correlation
coph_corr_coeff <- copheneticCorrelation(consensus_matrix)
cat(coph_corr_coeff)

acabassi/klic documentation built on Aug. 7, 2020, 6:56 p.m.