IntNMF (version 1.3.0)

SilhouettePlot: A function to plot silhouette width

Description

Given the integrative NMF fit object, the function creates silhouette width plot with different colors for different cluster groups.

Usage

SilhouettePlot(fit, cluster.col = NULL)

Value

Silhouette width plot is returned together with mean silhouette width for each group, overall silhouette width and summary statistics.

Arguments

fit

A nmf.mnnals fit object

cluster.col

Colors for the cluster groups. If NULL, default colors are used.

Author

Prabhakar Chalise, Rama Raghavan, Brooke Fridley

References

Rousseeue PJ (1987). Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20:53-65

Examples

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)
SilhouettePlot(fit,cluster.col=NULL)