Biomedical research increasingly involves examination of huge data sets. Introduction of new high- throughput sequencing technologies has led to production of new genome sequence for dozens of plants and animals and prompted major efforts to sequence individual human genomes. To take full advantage of these new large-scale data sets, researchers require flexible, user-friendly software that supports interactive, in-depth exploration of data at different levels of detail, ranging from chromosomes to individual base pairs. The Integrated Genome Browser (IGB) is a desktop, java-based genome browser implemented that implements innovative yet practical visualization techniques designed to help scientists explore genome-scale data sets, ultimately leading to better treatments for disease as scientists use IGB to achieve deeper insight into genes and genomes. This project will continue to develop the IGB software, adding new data integration and display features users have requested and which the IGB developers foresee will become increasingly important in the face of on-going and rapid technological change in genomics. Major improvements will include migrating the IGB graphical user interface to JavaFX, a toolkit released as part of Java 8 that replaces the Swing toolkit; speed and memory improvements for interactive display of large datasets; integration with cloud-based data storage resources; an all-new editing capability enabling users to annotate genomic scenes with new features inferred from data; and a new interactive alternative splicing visualization. The project will develop and harden the Integrated Genome Browser Application Programming Interface (API) for developers, transforming IGB into a flexible and easy-to-use framework for building and distributing all-new visualizations as IGB Apps, OSGi plug-ins that users will access via a new IGB App Store. To maximize project impact, we will accelerate user training and outreach, using social media, on-line training, and in-person workshops to help researchers develop deeper insight into bioinformatics analysis through visualization. This project will grow the IGB user community, which includes scientists working with data, programmers seeking to build powerful new tools, and bioinformatics analysts seeking easy ways to incorporate visualization into data analysis pipelines.

Public Health Relevance

Methods for generating genome-scale data sets are becoming cheaper and more accessible. We are rapidly approaching a time when public health professionals will be able to survey the genomes of large numbers of people and relate genotype with disease susceptibility, overall health, and outcomes from specific treatments. However, to take advantage of these data, scientists need good visualization software that makes exploring and analyzing the data easier to accomplish. This project will develop user- friendly yet innovative visualization and data sharing software that will accelerate the pace of discovery in the biosciences and ultimately lead to critical discoveries about the human genome and the role it plays in human health.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Biodata Management and Analysis Study Section (BDMA)
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Ravichandran, Veerasamy
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University of North Carolina Charlotte
Biostatistics & Other Math Sci
Other Domestic Higher Education
United States
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