choose_stable_clusters: Choose stable clusters based on ECC and frequency

In Core-Bioinformatics/ClustAssess: Tools for Assessing Clustering

Choose stable clusters based on ECC and frequency

Description

Filter the list of clusters obtained by the automatic ClustAssess pipeline using the ECC and frequency thresholds. The ECC threshold is meant to filter out the partitions that are highly sensitive to the change of the random seed, while the purpose of the frequency threshold is to assure a statistical significance of the inferred stability.

Usage

choose_stable_clusters(
  clusters_list,
  ecc_threshold = 0.9,
  freq_threshold = 30,
  summary_function = mean
)

Arguments

clusters_list	List of clusters obtained from the get_clusters_from_clustassess_object function.
ecc_threshold	Minimum ECC value to consider a cluster as stable. Default is 0.9.
freq_threshold	Minimum total frequency of the partitions to consider. Default is 30.
summary_function	Function to summarize the ECC values. Default is mean. To match the results from the ClustAssess Shiny App, use median.

Value

A list of stable clusters that satisfy the ECC and frequency.

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