create.template {flowMatch} | R Documentation

## Creating a template of a collection of FC samples

### Description

Create an object of class `Template` summarizes a group of samples belonging to same biological-class with a class-template. A template is represented by a collection of meta-clusters (`MetaCluster`) created from samples of same class. An object of class `Template` therefore stores a list of `MetaCluster` objects and other necessary parameters.

### Usage

      create.template(clustSamples, dist.type = "Mahalanobis", unmatch.penalty=999999, template.id = NA_integer_)

### Arguments

`clustSamples` | A list of `ClusteredSample` objects from which the template is created. The working examples describe how this objects are created by clustering FC samples.
`dist.type` | character, indicating the method with which the dissimilarity between a pair of clusters is computed. Supported dissimilarity measures are: 'Mahalanobis', 'KL' and 'Euclidean'. If this argument is not passed then 'Mahalanobis' distance is used by default.
`unmatch.penalty` | A numeric value denoting the penalty for leaving a cluster unmatched. This parameter should be already known or be estimated empirically estimated from data (see the reference for a discussion). Default is set to a very high value so that no cluster remains unmatched.
`template.id` | integer, denoting the index of the template (relative to other template). Default is NA_integer_

### Details

An object of class `Template` summarizes a group of samples belonging to same biological-class with a class-specific template. A template is represented by a collection of meta-clusters (`MetaCluster`) created from samples of same class. An object of class `Template` therefore stores a list of `MetaCluster` objects and other necessary parameters.

### Value

`dist.sample` returns a numeric value representing dissimilarity between a pair of samples. This value is equal to the summation of dissimilarities of the matched clusters and penalty for the unmatched clusters.

### 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`, `MetaCluster`

### 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)

    ## plot the template in terms of the meta-clusters
    ## option-1 (default): plot contours of each cluster of the meta-clusters
    plot(template)

    ## option-2: plot contours of each cluster of the meta-clusters with defined color
    plot(template, color.mc=c('blue','black','green3','red'))

    ## option-3: plot contours of the meta-clusters with defined color
    plot(template, plot.mc=TRUE, color.mc=c('blue','black','green3','red'))

    ## option-4: plot contours of each cluster of the meta-clusters with different colors for different samples
    plot(template, colorbysample=TRUE)

[Package flowMatch version 1.16.0 Index]