RotationCostBestGivenGraph {M3JF}

Evaluate the cluster number of multiple modality data

Description

Evaluate the cluster number of multiple modality data

Usage

RotationCostBestGivenGraph(W, NUMC = 2:5)

Arguments

W

a list of multiple modality data matrices

NUMC

a vector specify the data range to select best cluster number

Value

quality, a vector of rotation cost the same long as NUMC, where each element is the rotation cost value of the corresponding cluster number.

Examples

library(InterSIM)
library(SNFtool)
sim.data <- InterSIM(n.sample=100, cluster.sample.prop = c(0.20,0.30,0.27,0.23),
delta.methyl=5, delta.expr=5, delta.protein=5,p.DMP=0.2, p.DEG=NULL,
p.DEP=NULL,sigma.methyl=NULL, sigma.expr=NULL, sigma.protein=NULL,cor.methyl.expr=NULL,
cor.expr.protein=NULL,do.plot=FALSE, sample.cluster=TRUE, feature.cluster=TRUE)
sim.methyl <- sim.data$dat.methyl
sim.expr <- sim.data$dat.expr
sim.protein <- sim.data$dat.protein
temp_data <- list(sim.methyl, sim.expr, sim.protein)
dat <- lapply(temp_data, function(dd) {
  dd <- as.matrix(dd)
  dd1 <- dist2(dd,dd)
  W1 <- affinityMatrix(dd1, K = 10, sigma = 0.5)
})
W <- SNF(dat, 10, 10)
clu_eval <- RotationCostBestGivenGraph(W,2:10)