PAC: Calculate PAC Index

In dswatson/biomisc: Convenient wrappers for functions in bioinformatics analysis pipelines

Description

This function calculates the proportion of ambiguous clustering (PAC) for each value of k tested via consensus clustering.

Usage

PAC(cc, window = c(0.1, 0.9), plot = TRUE)

Arguments

cc	A list created by a call to ConsensusClusterPlus.
window	Lower and upper bounds for the consensus index sub-interval over which to calculate the PAC. Must be on (0, 1).
plot	Plot PAC scores as a bar plot? Default is TRUE.

Details

Consensus clustering is a method for testing the stability of cluster membership under resampling (Monti et al., 2003). Senbabaoglu et al. (2014) demonstrated that traditional methods for estimating optimal cluster number fail when probes are not independent, which they rarely are in omic data. The authors propose a new statistic, the proportion of ambiguous clustering (PAC), which measures the increase in the empirical CDF curve for each potential cluster number k over a user-defined sub-interval of the consensus index generated by the consensus cluster algorithm. The minimal PAC score for a given range of k is taken to be the optimal cluster number for that data set. The default settings of window = c(0.1, 0.9) are taken from the original PAC paper, and generally lead to stable results.

Value

A data frame with PAC scores for each value of k in cc.

References

Monti, S., Tamayo, P., Mesirov, J., & Golub, T. (2003). "Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data." Machine Learning, 52: 91-118. http://link.springer.com/article/10.1023/A:1023949509487

Senbabaoglu, Y., Michailidis, G. & Li, J.Z. (2014). "Critical limitations of consensus clustering in class discovery." Scientific Reports, 4:6207. http://www.nature.com/articles/srep06207

Examples

# Build consensus cluster object
library(ConsensusClusterPlus)
mat <- matrix(rnorm(1000 * 10), nrow = 1000, ncol = 10)
cc <- ConsensusClusterPlus(mat, maxK = 5)

# Run PAC()
PAC(cc)

dswatson/biomisc documentation built on May 15, 2019, 4:52 p.m.