hopach: Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH)

The HOPACH clustering algorithm builds a hierarchical tree of clusters by recursively partitioning a data set, while ordering and possibly collapsing clusters at each level. The algorithm uses the Mean/Median Split Silhouette (MSS) criteria to identify the level of the tree with maximally homogeneous clusters. It also runs the tree down to produce a final ordered list of the elements. The non-parametric bootstrap allows one to estimate the probability that each element belongs to each cluster (fuzzy clustering).

Getting started

Package details

AuthorKatherine S. Pollard, with Mark J. van der Laan <laan@stat.berkeley.edu> and Greg Wall
Bioconductor views Clustering
MaintainerKatherine S. Pollard <katherine.pollard@gladstone.ucsf.edu>
LicenseGPL (>= 2)
URL http://www.stat.berkeley.edu/~laan/ http://docpollard.org/
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


Try the hopach package in your browser

Any scripts or data that you put into this service are public.

hopach documentation built on Nov. 8, 2020, 4:54 p.m.