Visualization of large influenza virus sequence datasets using adaptively aggregated trees with sampling-based subscale representation.

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

SUBMITTER: Zaslavsky L 

PROVIDER: S-EPMC2416652 | biostudies-literature | 2008 May

REPOSITORIES: biostudies-literature