Whole Genome Sequencing Analysis: Comprehensive Capture of Genetic Variants

全基因组测序分析：全面捕获遗传变异

• 批准号: 1649847
• 负责人: Xihong Lin
• 金额: $ 2.85万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-15 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1649847&HistoricalAwards=false
• 关键词: Whole; Genome; Sequencing; Analysis; Comprehensive

The Program in Quantitative Genomics (PQG) at Harvard T.H. Chan School of Public Health is hosting the 2016 conference, "Whole Genome Sequencing Analysis: Comprehensive Capture of Genetic Variants", to be held November 3-4, 2016 at the Joseph B. Martin Conference Center at Harvard Medical School in Boston, MA. This is the tenth in a very successful conference series on emerging statistical and computational issues in genetics and genomics. The explosion of massive information about the human genome, including Whole Genome Sequencing data, presents extraordinary challenges in data processing, integration, analysis, and interpretation of results. A large number of Whole Genome Sequencing (WGS) samples are being generated by the community through the Genome Sequencing Program of the National Human Genome Research Institute, the TopMED Program of the National Heart, Lung and Blood Institute, and the Precision Medicine Initiative. Analysis of WGS data requires integration of statistical genetics and genomics, computational biology and population genetics, and existing statistical and computational techniques are not directly applicable. There is a critical need to discuss emerging quantitative issues at the forefront of scientific exploration, and to promote the development of innovative and scalable statistical and computational methods for analyzing massive whole genome sequencing data. The conference is open to the whole research community and particularly encourages participation of junior faculty and researchers, postdoctoral fellows, students, and women and minorities. The participants will discuss and critique existing quantitative methods, discuss in-depth emerging statistical and quantitative issues, and identify priorities for future research in the analysis of WGS data. The research presented will be broadly disseminated in publications in scientific journals and websites. The conference will focus on the following three topics of critical importance in whole genome sequencing analysis: (1) path to genomics; (2) scaling up phenotypes; (3) new horizons in population genetics. The first topic discusses statistical and computational methods for rare variant analysis by incorporating functional and regulatory information. The second topic discusses analysis of multiple phenotypes to boost the power for association, and to understand how different phenotypes relate genetically and reveal causal pathways. The third topic discusses new opportunities in population genetics, and the use of this knowledge in understanding human disease biology and etiology. A key feature of the conference is to provide a timely and interactive platform for cross-disciplinary senior and junior investigators, including statistical geneticists, computational biologists, population geneticists, genetic epidemiologists, molecular biologists, and clinical scientists, to discuss these analytic challenges for WGS data. For more information, visit https://www.hsph.harvard.edu/2016-pqg-conference/ .

哈佛公共卫生学院的定量基因组学项目（PQG）将于2016年11月3日至4日在马萨诸塞州波士顿哈佛医学院的Joseph B. Martin会议中心举办“全基因组测序分析：遗传变异的全面捕获”会议。这是一个非常成功的关于遗传学和基因组学中新兴统计和计算问题的系列会议的第十次会议。包括全基因组测序数据在内的大量人类基因组信息的爆炸，在数据处理、整合、分析和结果解释方面提出了非凡的挑战。通过国家人类基因组研究所的基因组测序计划、国家心肺血液研究所的TopMED计划和精准医学倡议，社区正在生成大量的全基因组测序（WGS）样本。WGS数据的分析需要统计遗传学和基因组学、计算生物学和群体遗传学的结合，现有的统计和计算技术并不直接适用。迫切需要在科学探索的前沿讨论新出现的定量问题，并促进创新和可扩展的统计和计算方法的发展，以分析大量的全基因组测序数据。会议向整个研究界开放，特别鼓励青年教师和研究人员、博士后、学生、妇女和少数民族的参与。与会者将讨论和批评现有的定量方法，深入讨论新出现的统计和定量问题，并确定未来研究WGS数据分析的优先事项。所提出的研究将在科学期刊和网站的出版物中广泛传播。会议将集中讨论三个在全基因组测序分析中至关重要的主题：(1)基因组学之路；(2)放大表型；(3)群体遗传学的新视野。第一个主题讨论了通过结合功能和调节信息进行罕见变异分析的统计和计算方法。第二个主题讨论了对多种表型的分析，以提高关联能力，并了解不同表型如何在遗传上相关并揭示因果途径。第三个主题讨论了群体遗传学的新机遇，以及利用这些知识来理解人类疾病生物学和病因学。会议的一个关键特点是为包括统计遗传学家、计算生物学家、群体遗传学家、遗传流行病学家、分子生物学家和临床科学家在内的跨学科高级和初级研究人员提供一个及时和互动的平台，讨论WGS数据的这些分析挑战。欲了解更多信息，请访问https://www.hsph.harvard.edu/2016-pqg-conference/。