title: Web-based visual analysis for high-throughput genomics.
abstract: BACKGROUND
  Visualization plays an essential role in genomics research by making it possible to observe correlations and trends in large datasets as well as communicate findings to others. Visual analysis, which combines visualization with analysis tools to enable seamless use of both approaches for scientific investigation, offers a powerful method for performing complex genomic analyses. However, there are numerous challenges that arise when creating rich, interactive Web-based visualizations/visual analysis applications for high-throughput genomics. These challenges include managing data flow from Web server to Web browser, integrating analysis tools and visualizations, and sharing visualizations with colleagues.
  
  
  RESULTS
  We have created a platform simplifies the creation of Web-based visualization/visual analysis applications for high-throughput genomics. This platform provides components that make it simple to efficiently query very large datasets, draw common representations of genomic data, integrate with analysis tools, and share or publish fully interactive visualizations. Using this platform, we have created a Circos-style genome-wide viewer, a generic scatter plot for correlation analysis, an interactive phylogenetic tree, a scalable genome browser for next-generation sequencing data, and an application for systematically exploring tool parameter spaces to find good parameter values. All visualizations are interactive and fully customizable. The platform is integrated with the Galaxy (http://galaxyproject.org) genomics workbench, making it easy to integrate new visual applications into Galaxy.
  
  
  CONCLUSIONS
  Visualization and visual analysis play an important role in high-throughput genomics experiments, and approaches are needed to make it easier to create applications for these activities. Our framework provides a foundation for creating Web-based visualizations and integrating them into Galaxy. Finally, the visualizations we have created using the framework are useful tools for high-throughput genomics experiments.
authors.affiliation: Department of Biology, Emory University, 1510 Clifton Road NE, Atlanta, GA 30322, USA.
authors.forename: Jeremy
authors.initials: J
authors.lastname: Goecks
authors.forename: Carl
authors.initials: C
authors.lastname: Eberhard
authors.forename: Tomithy
authors.initials: T
authors.lastname: Too
authors.forename: Anton
authors.initials: A
authors.lastname: Nekrutenko
authors.forename: James
authors.initials: J
authors.lastname: Taylor
mesh_terms: D003196:Computer Graphics; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D033181:Information Dissemination; D020407:Internet; D010802:Phylogeny; D011642:Publications; D013223:Statistics as Topic / Q000379:methods*