PomaClust: Cluster Analysis

In pcastellanoescuder/POMA: Tools for Omics Data Analysis

Cluster Analysis

Description

PomaClust performs a k-means clustering and plots the results in a classical multidimensional scaling (MDS) plot.

Usage

PomaClust(
  data,
  method = "euclidean",
  k = NA,
  k_max = floor(min(dim(data))/2),
  show_clusters = TRUE,
  labels = FALSE
)

Arguments

data	A SummarizedExperiment object.
method	Character. Indicates the distance method to perform MDS. Options are "euclidean", "maximum", "manhattan", "canberra" and "minkowski". See ?dist().
k	Numeric. Indicates the number of clusters (default is NA). The optimal number of clusters will be used by default.
k_max	Numeric. Indicates the number of clusters among which the optimal k will be selected.
show_clusters	Logical. Indicates if clusters should be plotted or not.
labels	Logical. Indicates if sample names should be plotted or not.

Value

A list with results including plots and tables.

Author(s)

Pol Castellano-Escuder

Examples

data("st000284")

PomaClust(st000284)

pcastellanoescuder/POMA documentation built on March 15, 2024, 10:08 p.m.