PAC (version 1.1.4)

aggregateData: Aggregates results from the clustering and merging step.

Description

Aggregates results from the clustering and merging step.

Usage

aggregateData(dataInput, labelsInput)

Arguments

dataInput

Data matrix, with first column being SampleID.

labelsInput

cluster labels from PAC.

Value

The aggregated data of dataInput, with average signal levels for all clusters and sample combinations.

Examples

# NOT RUN {
n = 5e3                       # number of observations
p = 1                         # number of dimensions
K = 3                         # number of clusters
w = rep(1,K)/K                # component weights
mu <- c(0,2,4)                # component means
sd <- rep(1,K)/K              # component standard deviations
g <- sample(1:K,prob=w,size=n,replace=TRUE)   # ground truth for clustering
X <- as.matrix(rnorm(n=n,mean=mu[g],sd=sd[g]))
y <- PAC(X, K)
X2<-as.matrix(rnorm(n=n,mean=mu[g],sd=sd[g]))
y2<-PAC(X2,K)
X<-cbind("Sample1", as.data.frame(X)); colnames(X)<-c("SampleID", "Value")
X2<-cbind("Sample2", as.data.frame(X2)); colnames(X2)<-c("SampleID", "Value")
aggregateData(rbind(X,X2),c(y,y2))
# }