CoeViz: A Web-Based Integrative Platform for Interactive Visualization of Large Similarity and Distance Matrices

Frazier N. Baker and Aleksey Porollo
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Frazier N. Baker: Department of Electrical Engineering and Computing Systems, University of Cincinnati, Cincinnati, OH 45221, USA
Aleksey Porollo: Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA

Data, 2018, vol. 3, issue 1, 1-10

Abstract: Similarity and distance matrices are general data structures that describe reciprocal relationships between the objects within a given dataset. Commonly used methods for representation of these matrices include heatmaps, hierarchical trees, dimensionality reduction, and various types of networks. However, despite a well-developed foundation for the visualization of such representations, the challenge of creating an interactive view that would allow for quick data navigation and interpretation remains largely unaddressed. This problem becomes especially evident for large matrices with hundreds or thousands objects. In this work, we present a web-based platform for the interactive analysis of large (dis-)similarity matrices. It consists of four major interconnected and synchronized components: a zoomable heatmap, interactive hierarchical tree, scalable circular relationship diagram, and 3D multi-dimensional scaling (MDS) scatterplot. We demonstrate the use of the platform for the analysis of amino acid covariance data in proteins as part of our previously developed CoeViz tool. The web-platform enables quick and focused analysis of protein features, such as structural domains and functional sites.

Keywords: distance matrix; similarity matrix; interactive visualization; zoomable heatmap; interactive dendrogram; circular relationship diagram; multi-dimensional scaling; CoeViz (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2018
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