reconstruct_recursive: Apply a clustering algorithm recursively to a given time...

In MultIS: Reconstruction of Clones from Integration Site Readouts and Visualization

Description

Apply a clustering algorithm recursively to a given time course.

Usage

reconstruct_recursive(
  readouts,
  method = "kmedoids",
  sim = MultIS::get_similarity_matrix(readouts = readouts, upper = TRUE),
  split_similarity = 0.7,
  combine_similarity = 0.9,
  use_silhouette = TRUE,
  cluster_obj = FALSE
)

Arguments

readouts	The time course for which to find clusters.
method	Either "kmedoids", "kmeans" or any string permitted as a method for stats::hclust.
sim	A similarity matrix used with all methods except "kmeans".
split_similarity	Similarity Threshold. If any two elements within a cluster are below this threshold, another split is initiated.
combine_similarity	After Splitting, a combination phase is activated. If any two elements between two clusters have a similarity higher than this threshold, the cluster are combined.
use_silhouette	If TRUE, silhouette is used to define number of cluster during splitting, otherwise cluster are always split into two new clusters.
cluster_obj	If TRUE, a clusterObject with the readouts, similarity and clustering is returned.

Value

A matrix with two columns: "Clone" and "IS" or if cluster_obj = TRUE a cluster object, which can be used to plot the clustering.

MultIS documentation built on Aug. 6, 2021, 5:07 p.m.