XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

BMC Bioinformatics
Sehi L'YiJinwook Seo

Abstract

Though cluster analysis has become a routine analytic task for bioinformatics research, it is still arduous for researchers to assess the quality of a clustering result. To select the best clustering method and its parameters for a dataset, researchers have to run multiple clustering algorithms and compare them. However, such a comparison task with multiple clustering results is cognitively demanding and laborious. In this paper, we present XCluSim, a visual analytics tool that enables users to interactively compare multiple clustering results based on the Visual Information Seeking Mantra. We build a taxonomy for categorizing existing techniques of clustering results visualization in terms of the Gestalt principles of grouping. Using the taxonomy, we choose the most appropriate interactive visualizations for presenting individual clustering results from different types of clustering algorithms. The efficacy of XCluSim is shown through case studies with a bioinformatician. Compared to other relevant tools, XCluSim enables users to compare multiple clustering results in a more scalable manner. Moreover, XCluSim supports diverse clustering algorithms and dedicated visualizations and interactions for different types of clustering ...Continue Reading

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Citations

Sep 4, 2015·BMC Bioinformatics·Jan AertsDaniel Weiskopf
Oct 30, 2019·BMC Bioinformatics·Rodolfo S Allendes OsorioKenji Mizuguchi
Jun 18, 2021·Computers in Biology and Medicine·Evangelos KaratzasGeorgios A Pavlopoulos

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Software Mentioned

KMeans
Matchmaker
JRE
OPTICS
HCE
Cluster
KMeans Clustering
iGPSe
CComViz
Parallel Coordinate Plot

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