PomaClust {POMA} | R Documentation

## Cluster Analysis

### Description

This function performs a classical multidimensional scaling (MDS) using all features in the data and computes a cluster analysis for `k` clusters. Then, the calculated clusters will be represented on a MDS plot.

### Usage

    PomaClust(
      data,
      method = "euclidean",
      k = NA,
      k_max = 15,
      show_clusters = TRUE,
      labels = FALSE,
      show_group = FALSE
    )

### Arguments

`data` | A MSnSet object. First `pData` column must be the subject group/type.
`method` | Distance measure method to perform MDS. Options are "euclidean", "maximum", "manhattan", "canberra" and "minkowski". See `?dist()`.
`k` | Number of clusters (default is `NA`). The optimum number of clusters will be used by default.
`k_max` | Number of clusters among which the optimal one will be selected.
`show_clusters` | Logical indicating if clusters should be plotted or not. If this parameter is set to `FALSE` the resultant plot will be a classical 2-dimension MDS plot.
`labels` | Logical indicating if sample names should be plotted or not.
`show_group` | Logical indicating if the original sample group from pData should be plotted instead of sample ID or not. Only works if labels is set to `TRUE`.

### Value

A list with the results.

### Author(s)

Pol Castellano-Escuder

### Examples

    data("st000284")

    PomaClust(st000284)

[Package POMA version 1.0.0 Index]