IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v3y2018i1p4-d126783.html
   My bibliography  Save this article

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

Author

Listed:
  • Frazier N. Baker

    (Department of Electrical Engineering and Computing Systems, University of Cincinnati, Cincinnati, OH 45221, USA
    Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA)

  • Aleksey Porollo

    (Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
    Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
    Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA)

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.

Suggested Citation

  • Frazier N. Baker & Aleksey Porollo, 2018. "CoeViz: A Web-Based Integrative Platform for Interactive Visualization of Large Similarity and Distance Matrices," Data, MDPI, vol. 3(1), pages 1-10, January.
  • Handle: RePEc:gam:jdataj:v:3:y:2018:i:1:p:4-:d:126783
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/3/1/4/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2306-5729/3/1/4/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jdataj:v:3:y:2018:i:1:p:4-:d:126783. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.