IterClust: a statistical framework for iterative clustering analysis.
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ABSTRACT:
SUBMITTER: Ding H
PROVIDER: S-EPMC6084607 | biostudies-literature | 2018 Aug
REPOSITORIES: biostudies-literature
Publications
iterClust: a statistical framework for iterative clustering analysis.
Ding Hongxu H Wang Wanxin W Califano Andrea A
Bioinformatics (Oxford, England) 20180801 16
<h4>Motivation</h4>In a scenario where populations A, B1 and B2 (subpopulations of B) exist, pronounced differences between A and B may mask subtle differences between B1 and B2.<h4>Results</h4>Here we present iterClust, an iterative clustering framework, which can separate more pronounced differences (e.g. A and B) in starting iterations, followed by relatively subtle differences (e.g. B1 and B2), providing a comprehensive clustering trajectory.<h4>Availability and implementation</h4>iterClust ...[more]
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