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]