Leonid Zaslavsky1, Yiming Bao, Tatiana A Tatusova. 1. National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. zaslavsk@ncbi.nlm.nih.gov
Abstract
BACKGROUND: With the amount of influenza genome sequence data growing rapidly, researchers need machine assistance in selecting datasets and exploring the data. Enhanced visualization tools are required to represent results of the exploratory analysis on the web in an easy-to-comprehend form and to facilitate convenient information retrieval. RESULTS: We developed an approach to visualize large phylogenetic trees in an aggregated form with a special representation of subscale details. The initial aggregated tree representation is built with a level of resolution automatically selected to fit into the available screen space, with terminal groups selected based on sequence similarity. The default aggregated representation can be refined by users interactively.Structure and data variability within terminal groups are displayed using small trees that have the same vertical size as the text annotation of the group. These subscale representations are calculated using systematic sampling from the corresponding terminal group. The aggregated tree containing terminal groups can be annotated using aggregation of structured metadata, such as seasonal distribution, geographic locations, etc. AVAILABILITY: The algorithms are implemented in JavaScript within the NCBI Influenza Virus Resource 1.
BACKGROUND: With the amount of influenza genome sequence data growing rapidly, researchers need machine assistance in selecting datasets and exploring the data. Enhanced visualization tools are required to represent results of the exploratory analysis on the web in an easy-to-comprehend form and to facilitate convenient information retrieval. RESULTS: We developed an approach to visualize large phylogenetic trees in an aggregated form with a special representation of subscale details. The initial aggregated tree representation is built with a level of resolution automatically selected to fit into the available screen space, with terminal groups selected based on sequence similarity. The default aggregated representation can be refined by users interactively.Structure and data variability within terminal groups are displayed using small trees that have the same vertical size as the text annotation of the group. These subscale representations are calculated using systematic sampling from the corresponding terminal group. The aggregated tree containing terminal groups can be annotated using aggregation of structured metadata, such as seasonal distribution, geographic locations, etc. AVAILABILITY: The algorithms are implemented in JavaScript within the NCBI Influenza Virus Resource 1.
Authors: Yiming Bao; Pavel Bolotov; Dmitry Dernovoy; Boris Kiryutin; Leonid Zaslavsky; Tatiana Tatusova; Jim Ostell; David Lipman Journal: J Virol Date: 2007-10-17 Impact factor: 5.103
Authors: Elodie Ghedin; Naomi A Sengamalay; Martin Shumway; Jennifer Zaborsky; Tamara Feldblyum; Vik Subbu; David J Spiro; Jeff Sitz; Hean Koo; Pavel Bolotov; Dmitry Dernovoy; Tatiana Tatusova; Yiming Bao; Kirsten St George; Jill Taylor; David J Lipman; Claire M Fraser; Jeffery K Taubenberger; Steven L Salzberg Journal: Nature Date: 2005-10-05 Impact factor: 49.962
Authors: Wolfgang Resch; Leonid Zaslavsky; Boris Kiryutin; Michael Rozanov; Yiming Bao; Tatiana A Tatusova Journal: BMC Microbiol Date: 2009-04-02 Impact factor: 3.605