An adaptive resolution tree visualization of large influenza virus sequence datasets

Authors:
Leonid Zaslavsky;Yiming Bao;Tatiana A. Tatusova
Affiliations:
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD;National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD;National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD
Venue:
ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
Year:
2007

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Abstract

Rapid growth of the amount of influenza genome sequence data requires enhancing exploratory analysis tools. Results of the preliminary analysis should be represented in an easy-to-comprehend form and allow convenient manipulation of the data. We developed an adaptive approach to visualization of large sequence datasets on the web. A dataset is presented in an aggregated tree form with special representation of sub-scale details. The representation is calculated from the full phylogenetic tree and the amount of available screen space. Metadata, such as distribution over seasons or geographic locations, are aggregated/refined consistently with the tree. The user can interactively request further refinement or aggregation for different parts of the tree. The technique is implemented in Javascript on client site. It is a part of the new AJAX-based implementation of the NCBI Influenza Virus Resource.