A fundamental challenge in human disease genetics is separating the small minority of variants that underlie a disease phenotype from the overwhelming majority of variants that are irrelevant to the phenotype. Resolving the genetic basis of rare diseases has been relatively fruitful despite this challenge, thanks to the fact that they are primarily caused by loss of function variants in a single gene and to the tremendous technological advances in DNA sequencing. However, despite many successes, the genetic basis of thousands of Mendelian disorders remains unknown and hundreds of new Mendelian disorders are described each year. Moreover, less than half of the Mendelian disorders studied are resolved after sequencing of affected families. Based on our experience in diagnosing rare diseases and in developing research software in this domain, we argue that existing commercial tools are both inadequate and expensive. Research pipelines for rare disease require substantial computational expertise and the integration of diverse genome annotations and algorithms for variant prioritization. The technical complexity of such pipelines inhibits discovery from researchers with substantial disease knowledge yet limited computational resources or experience. Therefore, our goal is to build a scalable, interactive, state-of-the-art software platform that will democratize the process of gene discovery in studies of Mendelian and other rare diseases. Our first Specific Aim is to create GxBrowse: an open source, interactive platform for rare disease discovery, drawing on the strengths of GEMINI, xBrowse, and the Exome Aggregation Consortium, three widely used tools and resources developed in our laboratories. Secondly, we will maximize GxBrowse?s performance, scalability, and accessibility to facilitate future rare disease research, especially as research in this area transitions from exome to whole genome sequencing. Lastly, we will provide innovative strategies for variant interpretation, visualization and data sharing to dramatically increase the rate of diagnosis and gene discovery. The GxBrowse platform will address fundamental analytical challenges in gene discovery for rare Mendelian diseases, and make a powerful and scalable open-source toolkit for rare disease analysis accessible to a wide range of researchers. We anticipate that GxBrowse will empower many research labs and become invaluable to future discoveries in larger NIH-funded efforts such as the Centers for Mendelian Genomics and the Undiagnosed Diseases Network.
Increasing the rate at which rare genetic disorders are resolved depends upon improved computational strategies and standardized analytical approaches. We propose to build an interactive, state of the art software platform that will democratize the process of gene discovery in studies of Mendelian and other rare diseases. By integrating crucial reference datasets and new algorithms with innovative visualization strategies, the software we develop will empower many research labs and become invaluable to future discoveries in rare disease genetics.
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