Biomedical research increasingly involves examination of huge data sets. In recent years, introduction of new high-throughput sequencing technologies have 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), used by more than 3,500 scientists worldwide, 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. Second, the project will implement improvements designed to enhance the productivity of IGB power users, researchers who typically spend many hours per day using the software to explore data sets they or their collaborators have created or obtained from public repositories. These improvements include: enhancing user's ability to invoke IGB from command line """"""""scripts,"""""""" supporting IGB interoperability with external analysis tools, saving and restoring sessions, and improving techniques for invoking IGB from Web pages via IGB links. The project will also continue development and maintenance of the Genoviz Software Development Kit (SDK), the library of software components that underlies the advanced visualization capabilities such as animated zooming that IGB users most appreciate in the software. By continuing to maintain and develop the Genoviz SDK, the project will make IGB a more robust and flexible software application while also giving developers powerful new tools for building advanced visualization software for scientists.

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 genes and genomes and the roles they play in disease processes and maintaining 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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Raines, Tracy; Blakley, Ivory C; Tsai, Yu-Chang et al. (2016) Characterization of the cytokinin-responsive transcriptome in rice. BMC Plant Biol 16:260
Estrada, April D; Freese, Nowlan H; Blakley, Ivory C et al. (2015) Analysis of pollen-specific alternative splicing in Arabidopsis thaliana via semi-quantitative PCR. PeerJ 3:e919
Gupta, Vikas; Estrada, April D; Blakley, Ivory et al. (2015) RNA-Seq analysis and annotation of a draft blueberry genome assembly identifies candidate genes involved in fruit ripening, biosynthesis of bioactive compounds, and stage-specific alternative splicing. Gigascience 4:5
Loraine, Ann E; Blakley, Ivory Clabaugh; Jagadeesan, Sridharan et al. (2015) Analysis and visualization of RNA-Seq expression data using RStudio, Bioconductor, and Integrated Genome Browser. Methods Mol Biol 1284:481-501
Gulledge, Alyssa A; Vora, Hiral; Patel, Ketan et al. (2014) A protocol for visual analysis of alternative splicing in RNA-Seq data using integrated genome browser. Methods Mol Biol 1158:123-37
Liu, Ruolin; Loraine, Ann E; Dickerson, Julie A (2014) Comparisons of computational methods for differential alternative splicing detection using RNA-seq in plant systems. BMC Bioinformatics 15:364
Gulledge, Alyssa A; Roberts, April D; Vora, Hiral et al. (2012) Mining Arabidopsis thaliana RNA-seq data with Integrated Genome Browser reveals stress-induced alternative splicing of the putative splicing regulator SR45a. Am J Bot 99:219-31