cell.hclust {immunoClust} | R Documentation

## Hierarchical Model Based Clustering of Cell-events in the immunoClust-pipeline

### Description

Performs model based agglomerative clustering on cell event observations with weights. It is used in the interative cell event clustering approach of immunoClust to obtain an initial cluster membership for the EM(t)-iteration.

### Usage

    cell.hclust(data, weights=NULL)

### Arguments

`data` | The numeric N x P-dimensional data matrix to cluster. Each row contains a P-dimensional overservation vector.
`weights` | The N-dimensional vector of optional weights to be applied for the overservations.

### Details

This function is used internally in `cell.TestSubCluster` procedure of immunoClust.

### Value

A numeric (N-1) x 2-dimensional matrix which gives the minimum index for observations in each of the two clusters merged at the ith step in each row.

### Author(s)

Till Sörensen till-antoni.soerensen@charite.de

### References

Sörensen, T., Baumgart, S., Durek, P., Grützkau, A. and Häupl, T. immunoClust - an automated analysis pipeline for the identification of immunophenotypic signatures in high-dimensional cytometric datasets. Cytometry A (accepted).

### See Also

`cell.TestSubCluster`, `cell.process`

### Examples

    data(dat.fcs)
    inc <- sample(1:nrow(dat.fcs), 50)
    result <- cell.hclust(exprs(dat.fcs)[inc,])

[Package immunoClust version 1.19.4 Index]