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)