create_clustering: Create Clustering Object

In Core-Bioinformatics/ClustAssess: Tools for Assessing Clustering

Create Clustering Object

Description

Creates a Clustering object from the output of a clustering method.

Usage

create_clustering(clustering_result, ...)

## S4 method for signature 'numeric'
create_clustering(clustering_result, alpha = 0.9)

## S4 method for signature 'integer'
create_clustering(clustering_result, alpha = 0.9)

## S4 method for signature 'character'
create_clustering(clustering_result, alpha = 0.9)

## S4 method for signature 'factor'
create_clustering(clustering_result, alpha = 0.9)

## S4 method for signature 'matrix'
create_clustering(
  clustering_result,
  alpha = 0.9,
  ppr_implementation = "prpack",
  row_normalize = TRUE
)

## S4 method for signature 'Matrix'
create_clustering(
  clustering_result,
  alpha = 0.9,
  ppr_implementation = "prpack",
  row_normalize = TRUE
)

## S4 method for signature 'hclust'
create_clustering(
  clustering_result,
  alpha = 0.9,
  r = 1,
  rescale_path_type = "max",
  ppr_implementation = "prpack",
  dist_rescaled = FALSE
)

Arguments

clustering_result	The clustering result, either: A numeric/character/factor vector of cluster labels for each element. A samples x clusters matrix/Matrix::Matrix of nonzero membership values. An hclust object.
...	This argument is not used.
alpha	A numeric giving the personalized PageRank damping factor; 1 - alpha is the restart probability for the PPR random walk.
ppr_implementation	Choose a implementation for personalized page-rank calculation: "prpack": use PPR algorithms in igraph. "power_iteration": use power_iteration method.
row_normalize	Whether to normalize all rows in clustering_result so they sum to one before calculating ECS. It is recommended to set this to TRUE, which will lead to slightly different ECS values compared to clusim.
r	A numeric hierarchical scaling parameter.
rescale_path_type	A string; rescale the hierarchical height by: "max" : the maximum path from the root. "min" : the minimum path form the root. "linkage" : use the linkage distances in the clustering.
dist_rescaled	A logical: if TRUE, the linkage distances are linearly rescaled to be in-between 0 and 1.

Value

A Clustering object.

Functions

• create_clustering(numeric): Create Clustering Object from Numeric Vector

• create_clustering(integer): Create Clustering Object from Integer Vector

• create_clustering(character): Create Clustering Object from Character Vector

• create_clustering(factor): Create Clustering Object from Factor Vector

• create_clustering(matrix): Create Clustering Object from base matrix

• create_clustering(Matrix): Create Clustering Object from Matrix::Matrix

• create_clustering(hclust): Create Clustering Object from hclust

Core-Bioinformatics/ClustAssess documentation built on Dec. 19, 2024, 8:19 p.m.