cell.ME {immunoClust} | R Documentation

## immunoClust EM-iteration on Cell-events given initial Cluster Membership Assignment

### Description

Performs an EM-iteration on cell event observations given an initial cluster membership for the cell events and returns the fitted cluster information in an object of class `immunoClust`.

### Usage

    cell.ME(data, parameters=NULL, expName="immunoClust Experiment",
            history=NULL, state=NULL, label, B=50, tol=1e-5, modelName="mvt")

### Arguments

`data` | A numeric matrix, data frame of observations, or object of class flowFrame.
`parameters` | A character vector specifying the parameters (columns) to be included in clustering. When it is left unspecified, all the parameters will be used.
`expName` | The name of the clustering experiment.
`history` | experimental; unused so far.
`state` | experimental: unused so far.
`label` | The N-dimensional vector containing the initial cluster membership. A label-number of 0 for an event indicates that this event is not initially assigned to a cluster.
`B` | The maximum number of EMt-iterations.
`tol` | The tolerance used to assess the convergence of the EMt-algorithms.
`modelName` | Used mixture model; either `"mvt"` or `"mvn"` for a t- or Gaussian mixture model respectively.

### Value

The fitted clusters information in an object of class `immunoClust`.

### 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.EM`

### Examples

    data(dat.fcs)
    data(dat.exp)
    ## cell.clustering result for dat.fcs
    r1 <- dat.exp[[1]]
    summary(r1)
    ## apply model parameter to all (unfiltered) events
    dat.trans <- trans.ApplyToData(r1, dat.fcs)
    r2 <- cell.ME(dat.trans, parameters(r1), label=label(r1))
    summary(r2)

[Package immunoClust version 1.18.1 Index]