PAC {cola}R Documentation

The proportion of ambiguous clustering (PAC score)

Description

The proportion of ambiguous clustering (PAC score)

Usage

PAC(consensus_mat, x1 = 0.1, x2 = 0.9, class = NULL)

Arguments

consensus_mat

A consensus matrix.

x1

Lower bound to define "ambiguous clustering".

x2

Upper bound to define "ambihuous clustering".

class

class IDs. If it is provided, samples with silhouette score less than 5th percential are removed.

Details

The PAC score is defined as F(x2) - F(x1) where F(x) is the CDF of the consensus matrix.

Value

A single numeric vaule.

See

See https://www.nature.com/articles/srep06207 for explanation of PAC score.

Author(s)

Zuguang Gu <z.gu@dkfz.de>

Examples

data(cola_rl)
PAC(get_consensus(cola_rl[1, 1], k = 2))
PAC(get_consensus(cola_rl[1, 1], k = 3))
PAC(get_consensus(cola_rl[1, 1], k = 4))
PAC(get_consensus(cola_rl[1, 1], k = 5))
PAC(get_consensus(cola_rl[1, 1], k = 6))

[Package cola version 1.0.1 Index]