Reordering Hierarchical Tree Based on Bilateral Symmetric Distance

Minho Chae and James J Chen

PLOS ONE, 2011, vol. 6, issue 8, 1-7

Abstract: Background: In microarray data analysis, hierarchical clustering (HC) is often used to group samples or genes according to their gene expression profiles to study their associations. In a typical HC, nested clustering structures can be quickly identified in a tree. The relationship between objects is lost, however, because clusters rather than individual objects are compared. This results in a tree that is hard to interpret. Methodology/Principal Findings: This study proposes an ordering method, HC-SYM, which minimizes bilateral symmetric distance of two adjacent clusters in a tree so that similar objects in the clusters are located in the cluster boundaries. The performance of HC-SYM was evaluated by both supervised and unsupervised approaches and compared favourably with other ordering methods. Conclusions/Significance: The intuitive relationship between objects and flexibility of the HC-SYM method can be very helpful in the exploratory analysis of not only microarray data but also similar high-dimensional data.

Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0022546

DOI: 10.1371/journal.pone.0022546

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