| flowMatch-package {flowMatch} | R Documentation |
Matching cell populations and building meta-clusters and templates from a collection of FC samples.
| Package: | flowMatch |
| Type: | Package |
| Version: | 1.0 |
| Date: | 2013-08-01 |
| License: | GPL (>= 2) |
| LazyLoad: | yes |
Ariful Azad <aazad@purdue.edu>
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.
Azad, Ariful and Langguth, Johannes and Fang, Youhan and Qi, Alan and Pothen, Alex (2010), Identifying rare cell populations in comparative flow cytometry; Algorithms in Bioinformatics, Springer, 162-175.
## ------------------------------------------------
## 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)
## plot the template in terms of the meta-clusters
## option-1 (default): plot contours of each cluster of the meta-clusters
plot(template)