clusterByQuality {AneuFinder} | R Documentation

## Cluster based on quality variables

### Description

This function uses the mclust package to cluster the input samples based on various quality measures.

### Usage

    clusterByQuality(hmms, G = 1:9, itmax = c(100, 100),
      measures = c("spikiness", "entropy", "num.segments", "bhattacharyya",
      "complexity", "sos"), orderBy = "spikiness", reverseOrder = FALSE)

### Arguments

`hmms` | A list of `aneuHMM` objects or a character vector with files that contain such objects.
`G` | An integer vector specifying the number of clusters that are compared. See `Mclust` for details.
`itmax` | The maximum number of outer and inner iterations for the `Mclust` function. See `emControl` for details.
`measures` | The quality measures that are used for the clustering. Supported is any combination of `c('spikiness','entropy','num.segments','bhattacharyya','loglik','complexity','sos','avg.read.count','total.read.count','avg.binsize')`.
`orderBy` | The quality measure to order the clusters by. Default is `'spikiness'`.
`reverseOrder` | Logical indicating whether the ordering by `orderBy` is reversed.

### Details

Please see `getQC` for a brief description of the quality measures.

### Value

A `list` with the classification, parameters and the `Mclust` fit.

### Author(s)

Aaron Taudt

### See Also

`getQC`

### Examples

    ## Get a list of HMMs
    folder <- system.file("extdata", "primary-lung", "hmms", package="AneuFinderData")
    files <- list.files(folder, full.names=TRUE)
    cl <- clusterByQuality(files)
    ## Plot the clustering and print the parameters
    plot(cl$Mclust, what='classification')
    print(cl$parameters)
    ## Select files from the best 2 clusters for further processing
    best.files <- unlist(cl$classification[1:2])

[Package AneuFinder version 1.8.0 Index]