PomaClust: Cluster Analysis

Description Usage Arguments Value Author(s) Examples

View source: R/PomaClust.R

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

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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

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data("st000284")

PomaClust(st000284)

pcastellanoescuder/POMA documentation built on May 14, 2021, 11:07 p.m.