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.
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References
Fauci, A.S.: Race against time. Nature 435(7041), 423–424 (2005)
Ghedin, E., et al.: Large-scale sequencing of human influenza reveals the dynamic nature of viral genome evolution. Nature 437(7062), 1162–1166 (2005)
The National Center for Biotechnology Information (NIH/NLM/NCBI): The Influenza Virus Resource, http://www.ncbi.nlm.nih.gov/genomes/FLU/FLU.html
Bao, Y., et al.: NCBI Influenza Virus Resource. Manuscript in preparation. National Center for Biotechnology Information (2006)
Felsenstein, J.: Inferring Phylogenies, 1st edn. Cambridge University Press, Cambridge (Sept. 2003)
Mather, G.: Foundations of Perception, 1st edn. Psychology Press, Hove (Jan. 2006)
Baron, J.: Thinking and Deciding, 3rd edn. Cambridge University Press, Cambridge (Dec. 2000)
Card, S.K., Nation, D.: Degree-of-interest trees: A component of an attention-reactive user interface. In: Proc. Advanced Visual Interfaces (AVI), pp. 231–245 (2002)
Fekete, J.-D., Plaisant, C.: Interactive information visualization of a million items. In: Proc. InfoVis, pp. 117–124 (2002)
Lamping, J., Rao, R., Pirolli, P.: Focus+content technique based on hyperbolic geometry for viewing large hierarchies. In: Proc. CHI’95, pp. 401–408 (1995)
Rost, U., Bornberg-Bauer, E.: Treewiz: interactive exploration of huge trees. Bioinformatics 18(1), 109–114 (2002)
Beermann, D., Munznerz, T., Humphreysy, G.: Scalable, robust visualization of very large trees. In: Brodlie, K.W., Duke, D.J., Joy, K.I. (eds.) EUROGRAPHICS - IEEE VGTC Symposium on Visualization, pp. 1–8 (2005)
MacEachren, A.M.: How Maps Work: Representation, Visualization, and Design, 2nd rev. edn. Guilford, New York (June 2004)
Zakas, N.C., McPeak, J., Fawcett, J.: Professional Ajax, 1st edn. Wrox, Birmingham (Feb. 2006)
Mozilla Foundation: Resources related to the new HTML5 canvas element, http://developer.mozilla.org/en/docs/Category:HTML:Canvas
The World Wide Web Consortium (W3C): Scalable vector graphics (svg): Xml graphics for the web, http://www.w3.org/Graphics/SVG/
Mozilla Foundation: Mozilla svg project, http://www.mozilla.org/projects/svg/
Adobe Systems: Adobe SVG Viewer, http://www.adobe.com/svg/viewer/install/
The National Institute of Allergy and Infectious Diseases (NIAID): NIAID Launches Influenza Genome Sequencing Project. Press Release (November 2004), http://www3.niaid.nih.gov/news/newsreleases/2004/flugenome.htm
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Zaslavsky, L., Bao, Y., Tatusova, T.A. (2007). An Adaptive Resolution Tree Visualization of Large Influenza Virus Sequence Datasets. In: Măndoiu, I., Zelikovsky, A. (eds) Bioinformatics Research and Applications. ISBRA 2007. Lecture Notes in Computer Science(), vol 4463. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72031-7_18
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DOI: https://doi.org/10.1007/978-3-540-72031-7_18
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