PAC {cola} | R Documentation |
The proportion of ambiguous clustering (PAC score)
PAC(consensus_mat, x1 = 0.1, x2 = 0.9, class = NULL)
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. |
The PAC score is defined as F(x2) - F(x1) where F(x) is the CDF of the consensus matrix.
A single numeric vaule.
See https://www.nature.com/articles/srep06207 for explanation of PAC score.
Zuguang Gu <z.gu@dkfz.de>
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))