Next-generation sequencing technologies and their applications (e.g., ChIP-seq, HiC) are generating an astonishing amount of genomic, epigenomic and transcriptomic data, serving the scientific community a rich, growing resource and producing new types of reference (i.e., the reference epigenomes) in the """"""""post- genome"""""""" era. However, there is a serious bottleneck for investigators to take full advantage of these data for biomedical research. Conventional Genome Browsers limit biologists to examine a gene or a genomic region at a time, and limit them to compare at most a couple dozen datasets visually. Additional bioinformatics expertise is required to manipulate and analyze these data, and to compare investigators'own data with public data produced by consortiums. In this proposal, we introduce The Wash U Epigenome Browser and its associated visualization and analysis tools to give investigators a next- generation experience in exploring, manipulating and analyzing large genomic datasets. Our strategy is to combine state-of-the-art web technologies, programming practices and user interface design to deliver the most intuitive, easy-to-use, and comprehensive bioinformatics tools in the format of a next-generation Genome Browser.
In Specific Aim 1 we will develop and extend The Wash U Epigenome Browser as a visual bioinformatics engine that enables biologists to visualize hundreds of genome-wide datasets, annotate genomics data with metadata, visually navigate and manipulate the data, and easily generate testable hypothesis. If successful, it will produce an effective tool to accelerate scientific interpretation of large genomic data.
In Specific Aim 2 we will develop the Epigenome Browser to become versatile visualization systems that can rapidly evolve and adapt for new data type and new analysis. We will demonstrate the potential of rapid development to meet new visualization and analysis needs by solving two difficult problems: visualizing long-range chromatin interaction data and visualizing data on repeats and transposable elements. The Wash U Epigenome Browser and its associated visualization and analysis tools promise to revolutionize how biologists engage with large genomic and epigenomic datasets produced by next-generation technologies and will serve as a novel bioinformatics platform for diagnosis and treatment of disease.
New tools are needed to help investigators navigate and manipulate the enormous genomic and epigenomic data produced by modern sequencing-based technologies. We propose to develop a next- generation Epigenome Browser that works as a visual bioinformatics engine. Not only will this new Browser greatly enhance how investigators explore and take advantage of public consortium data, it will eventually help investigators make use of next-generation data for disease diagnosis and therapy.
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