template.tree: Plot the hierarchy of samples established while creating a...

In flowMatch: Matching and meta-clustering in flow cytometry

Description

All samples within a template are organized as binary tree. This function plots the hierarchy of samples established while creating a template-tree.

Usage

  template.tree(object, ...)

Arguments

object	An object of class Template. The working examples describe how a template is created from a collection of FC samples.
...	Other usual plotting related parameters.

Value

Returns a tree object of class hclust storing the hierarchy of the samples in the template.

Author(s)

Ariful Azad

References

Azad, Ariful and Pyne, Saumyadipta and Pothen, Alex (2012), Matching phosphorylation response patterns of antigen-receptor-stimulated T cells via flow cytometry; BMC Bioinformatics, 13 (Suppl 2), S10.

See Also

Template, create.template

Examples

 ## ------------------------------------------------
## load data
## ------------------------------------------------

library(healthyFlowData)
data(hd)

## ------------------------------------------------
## Retrieve each sample, clsuter it and store the
## clustered samples in a list
## ------------------------------------------------
set.seed(1234) # for reproducable clustering 
cat('Clustering samples: ')
clustSamples = list()
for(i in 1:length(hd.flowSet))
{
  cat(i, ' ')
  sample1 = exprs(hd.flowSet[[i]])
  clust1 = kmeans(sample1, centers=4, nstart=20)
  cluster.labels1 = clust1$cluster
  clustSample1 = ClusteredSample(labels=cluster.labels1, sample=sample1)
  clustSamples = c(clustSamples, clustSample1)
}

## ------------------------------------------------
## Create a template from the list of clustered samples and plot functions
## ------------------------------------------------

template = create.template(clustSamples)
summary(template)

## plot the tree denoting the hierarchy of the samples in a template
tree = template.tree(template)

  

flowMatch documentation built on Nov. 8, 2020, 8:02 p.m.