HCsnip: Semi-supervised adaptive-height snipping of the Hierarchical Clustering tree

Decompose given hierarchical clustering tree into non-overlapping clusters in a semi-supervised way by using available patients follow-up information as guidance. Contains functions for snipping HC tree, various cluster quality evaluation criteria, assigning new patients to one of the two given HC trees, testing the significance of clusters with permutation argument and clusters visualization using sample's molecular entropy.

Install the latest version of this package by entering the following in R:
AuthorAskar Obulkasim
Bioconductor views Clustering GeneExpression Microarray aCGH
Date of publicationNone
MaintainerAskar Obulkasim <askar703@gmail.com>
LicenseGPL (>= 2)

View on Bioconductor

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.