HCsnip: An R Package for Semi-supervised Snipping of the Hierarchical Clustering Tree.

ABSTRACT: Hierarchical clustering (HC) is one of the most frequently used methods in computational biology in the analysis of high-dimensional genomics data. Given a data set, HC outputs a binary tree leaves of which are the data points and internal nodes represent clusters of various sizes. Normally, a fixed-height cut on the HC tree is chosen, and each contiguous branch of data points below that height is considered as a separate cluster. However, the fixed-height branch cut may not be ideal in situations where one expects a complicated tree structure with nested clusters. Furthermore, due to lack of utilization of related background information in selecting the cutoff, induced clusters are often difficult to interpret. This paper describes a novel procedure that aims to automatically extract mean

SUBMITTER: Obulkasim A 

PROVIDER: S-EPMC4372030 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature