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A powerful web-based discovery platform for rare disease genetics

一个强大的基于网络的罕见疾病遗传学发现平台

基本信息

批准号：
9309875
负责人：
Daniel G MacArthur
金额：
$ 83.67万
依托单位：
BROAD INSTITUTE, INC.
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-13 至 2021-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9309875
关键词：
Address Adoption Affect Algorithms Architecture Area Candidate Disease Gene Code Communities Computer software Copy Number Polymorphism DNA sequencing Data Data Set Databases Diagnosis Disease Exons Family Frequencies Funding Future Gene Expression Profile Genes Genetic Genome Genomics Genotype Goals Hereditary Disease Hour Imagery Individual Internet Intuition Knowledge Laboratories Mendelian disorder Methods Minority Modeling Online Systems Performance Phenotype Probability Processed Genes Quality Control Rare Diseases Reporting Research Research Personnel Resources Sampling Secure Standardization System Techniques Testing Time Tissues Transcript United States National Institutes of Health Untranslated RNA Variant Visualization software base candidate validation clinical phenotype cloud based cohort computing resources cost data integration data modeling data sharing data visualization design disease phenotype empowered exome exome sequencing experience family support gene discovery genetic pedigree genome annotation genome sequencing graphical user interface human disease improved innovation insertion/deletion mutation loss of function online resource open source protein protein interaction research and development scale up skills software development success tool usability whole genome

项目摘要

PROJECT SUMMARY 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.

项目总结