Description Creating Object Slots Accessors Methods Author(s) See Also Examples
An object of class "Cluster
" represents a cluster or a cell population. We model a cluster with a normal distribution. An object of class "Cluster
" therefore represents a cluster with a mean vector, a covariance matrix and the size of the cluster.
An object of class Cluster
is usually created when constructing an object of class ClusteredSample
.
Unless you know exactly what you are doing, creating an object of class "Cluster
" using new
or using the constructor is discouraged.
An object of class "Cluster
" can be created using the following constructor
Cluster(size, center, cov, cluster.id = NA_integer_, sample.id=NA_integer_)
The arguments of the constructor bear usual meaning as described in the value section above.
An object of class "Cluster
" contains the following slots:
size
:An integer denoting the number of points (cells) present in the cluster.
center
:A numeric vector denoting the center of the cluster.
cov
:A matrix denoting the covariances of the underlying normal distribution of the cluster.
cluster.id
:The index of the cluster (relative to other clusters in same sample). Default is NA_integer_
.
sample.id
:The index of sample in which the cluster belongs to. Default is NA_integer_
.
All the slot accessor functions take an object of class Cluster
. I show usage of the first accessor function. Other functions can be called similarly.
get.size
:Returns the number of cells in the cluster.
Usage: get.size(object)
here object
is a Cluster
object.
get.center
:Returns the center of the cluster.
get.cov
:Returns the covariances matrix of the cluster.
get.cluster.id
:Returns the index of the cluster (relative to other clusters in same sample).
get.sample.id
:Returns the index of sample in which the cluster belongs to.
sample.id<-
:Set the index of sample in which the cluster belongs to.
Display details about the Cluster
object.
Return descriptive summary for each Cluster
object.
Usage: summary(Cluster)
Ariful Azad
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | ## An object of class "Cluster"" is usually created when constructing a "ClusteredSample".
## Unless you know exactly what you are doing, creating an object of class "Cluster"
## using new or using the constructor is discouraged.
## ------------------------------------------------
## load data and retrieve a sample
## ------------------------------------------------
library(healthyFlowData)
data(hd)
sample = exprs(hd.flowSet[[1]])
## ------------------------------------------------
## cluster sample using kmeans algorithm
## and retrive the parameters of the first cluster
## ------------------------------------------------
km = kmeans(sample, centers=4, nstart=20)
center1 = km$centers[1,]
# compute the covariance matrix of the first cluster
cov1 = cov(sample[km$cluster==1,])
size1 = length(which(km$cluster==1))
## ------------------------------------------------
## Create an object of class "Cluster"
## and show summary
## ------------------------------------------------
clust = Cluster(size=size1, center=center1, cov=cov1)
summary(clust)
|
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