meta.hclust {immunoClust} | R Documentation

## Hierarchical Meta-clustering of Cell-clusters in the immunoClust-pipeline

### Description

Performs agglomerative clustering on cell-clusters. It is used in the interative meta-clustering approach of immunoClust to obtain an initial meta-cluster membership for the EM(t)-iteration.

### Usage

    meta.hclust(P, N, W, M, S)

### Arguments

`P` | The number of parameters.
`N` | The number of clusters.
`W` | The N-dimensional vector with cluster weights, i.e. numbers of events in a cluster.
`M` | The N x P-dimensional vector with cluster means.
`S` | The N x P x P-dimensional vector with cluster covariance matrices.

### Details

This function is used internally in `meta.TestSubCluster` 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.

### Note

The merging distances need not to be monotonic increasing.

### 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

`meta.TestSubCluster`, `meta.process`

### Examples

    data(dat.exp)
    r <- dat.exp[[1]]
    #hcPairs <- meta.hclust(r@P, r@K, r@w, r@mu, t(apply(r@sigma,1,c)))
    hcPairs <- meta.hclust(npar(r), ncls(r), weights(r),
        mu(r), t(apply(sigma(r),1,c)))

[Package immunoClust version 1.24.0 Index]