kmeansClust {tomoda} | R Documentation

## K-Means clustering across sections

### Description

Performs K-Means clustering across sections in a `SummarizedExperiment` object.

### Usage

    kmeansClust(object, centers, matrix = "normalized", ...)

### Arguments

`object` | A `SummarizedExperiment` object.
`centers` | Integer, number of clusters, namely k.
`matrix` | Character, must be one of `"count"`, `"normalized"`, or `"scaled"`.
`...` | other parameters passed to `kmeans`.

### Value

A `SummarizedExperiment` object. The obtained cluster labels are saved in slot `meta`.

### See Also

`kmeans` for performing K-Means clustering on a matrix.

### Examples

    data(zh.data)
    zh <- createTomo(zh.data)
    zh <- kmeansClust(zh, 3)

    # Use scaled read counts to calculate distance
    zh <- scaleTomo(zh)
    zh <- kmeansClust(zh, 3, matrix="scaled")

[Package tomoda version 1.0.0 Index]