ClusterEntropy: A function to measure cluster entropy In IntNMF: Integrative Clustering of Multiple Genomic Dataset

Description

Given the true clustering assignment for the subjects, this function calculates cluster entropy index comparing with clustering assignment determined by integrative NMF algorithm. Smaller value of cluster entropy indicates better cluster predictive discrimination.

Usage

 `1` ```ClusterEntropy(ComputedClusters, TrueClasses) ```

Arguments

 `ComputedClusters` Clustering assignment determined by integrative NMF algorithm `TrueClasses` True clustering assignment of the subjects

Value

Cluster entropy index value

Author(s)

Prabhakar Chalise, Rama Raghavan, Brooke Fridley

References

Kim Hyunsoo and Park Haesun (2007). Sparse non-negative matrix factorization via alternating non-negativity constrained least squares for microarray data analysis. Bioinformatics, 23: 1495-1502.

Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24``` ```prop <- c(0.20,0.30,0.27,0.23) effect <- 2.5 sim.D <- InterSIM(n.sample=100,cluster.sample.prop=prop,delta.methyl=effect, delta.expr=effect,delta.protein=effect,p.DMP=0.25,p.DEG=NULL,p.DEP=NULL, do.plot=FALSE, sample.cluster=TRUE, feature.cluster=TRUE) dat1 <- sim.D\$dat.methyl dat2 <- sim.D\$dat.expr dat3 <- sim.D\$dat.protein true.cluster.assignment <- sim.D\$clustering.assignment ## Make all data positive by shifting to positive direction. ## Also rescale the datasets so that they are comparable. if (!all(dat1>=0)) dat1 <- pmax(dat1 + abs(min(dat1)), .Machine\$double.eps) dat1 <- dat1/max(dat1) if (!all(dat2>=0)) dat2 <- pmax(dat2 + abs(min(dat2)), .Machine\$double.eps) dat2 <- dat2/max(dat2) if (!all(dat3>=0)) dat3 <- pmax(dat3 + abs(min(dat3)), .Machine\$double.eps) dat3 <- dat3/max(dat3) # The function nmf.mnnals requires the samples to be on rows and variables on columns. dat <- list(dat1,dat2,dat3) fit <- nmf.mnnals(dat=dat,k=length(prop),maxiter=200,st.count=20,n.ini=15,ini.nndsvd=TRUE, seed=TRUE) ClusterEntropy(ComputedClusters=fit\$clusters, TrueClasses=true.cluster.assignment\$cluster.id) ```

IntNMF documentation built on May 1, 2019, 6:35 p.m.