Emerging Statistical and Quantitative Issues in Genomic Research in Health Sciences

健康科学基因组研究中新出现的统计和定量问题

• 批准号: 1833416
• 负责人: Xihong Lin
• 金额: $ 9万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1833416&HistoricalAwards=false
• 关键词: Emerging; Statistical; Quantitative; Issues; Genomic

The 2018 Conference of the Program in Quantitative Genomics (PQG), entitled "Biobanks: Study Design and Data Analysis" will take place at the Joseph B. Martin Conference Center at the Harvard Medical School from November 1-2, 2018. This is the first of three years of the Program in Quantitative Genomics (PQG) Conference series to be supported by this award. This long-standing conference series, open to the whole research community, focuses on timely interdisciplinary discussions on emerging statistical and computational challenges in genetic and genomic science. The focus of each conference changes to reflect the evolution of scientific frontiers. Key to the success of the series is its interdisciplinary nature, bringing quantitative and subject-matter scientists together to discuss statistical and quantitative issues that arise in cutting-edge genetic and genomic research in human disease. The impetus for the 2018 conference theme comes from the proliferation of large-scale biobanks worldwide, composed of massive genetic and genomic data, epidemiological data, Electronic Medical Records, wearable devices and imaging data. The use of biobanks is becoming an essential and potentially revolutionizing approach to biomedical research, with the capacity to improve the prevention, diagnosis, and treatment of a wide range of illnesses, and to advance personalized health. This conference aims at discussing key statistical and quantitative challenges in biobank studies, including biobank design to meet a wide array of needs, strategies for improving phenotyping accuracy, data harmonization across biobanks, and novel statistical and data science methods for analysis of biobank data. The conference is open to the whole research community and particularly encourages participation of junior faculty and researchers, postdoctoral fellows, students, women and members of underrepresented groups. 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 design and analysis of biobank data. The research presented will be broadly disseminated in publications in scientific journals and websites. For the 2018 PQG conference we have assembled an interdisciplinary team of speakers experienced in biobank development and study design, including statisticians, medical informaticians, geneticists, epidemiologists, and clinical scientists. Three emerging topics of substantial current interest include the design of population Biobanks; phenotyping and harmonization across biobanks; and biobank data analysis. The conference discussion will revolve around 1) examples of different types of biobanks including different examples of recruitment strategies, selection of genotype / technologies, genotype resources and future directions, design strategies: cross-section, longitudinal, representative probability sampling, and increasing diversity and expanding to the Americas, Africa and Asia; 2) issues of phenotyping and harmonization across biobanks including new methods for improving phenotyping, harmonization within and across biobanks, enriching phenotyping using registry data (time to event), combining different biobank/registry data across the world, bias and missing data, misclassification in electronic health records (EHR) and other design heterogeneity issues in EHR databases; and finally 3) issues related to data analysis methods, including how to make analysis computationally scalable, analysis of related samples and admixture samples, multiple phenotypes and PheWAS analysis, missing data, misclassification of phenotypes, handling small number of cases for some diseases, risk prediction, selection of appropriate controls, integrative analysis across biobanks, and integrative analysis of different data types (genotype and phenotype, or transcriptomic and metabolomic data) or replicating phenotypes across biobanks. For more information, see https://www.hsph.harvard.edu/2018-pqg-conference/This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

2018年定量基因组学(PQG)计划会议将于2018年11月1日至2日在哈佛医学院约瑟夫·B·马丁会议中心举行，题为《生物库：研究设计与数据分析》。这是该奖项支持的定量基因组学计划(PQG)系列会议三年中的第一年。这一长期的系列会议向整个研究界开放，重点是就遗传和基因组科学中新出现的统计和计算挑战进行及时的跨学科讨论。每次会议的重点都会发生变化，以反映科学前沿的演变。该系列成功的关键是它的跨学科性质，将定量和主题科学家聚集在一起，讨论在人类疾病的尖端遗传和基因组研究中出现的统计和定量问题。2018年大会主题的推动力来自全球大规模生物库的激增，这些生物库由海量遗传和基因组数据、流行病学数据、电子病历、可穿戴设备和成像数据组成。生物库的使用正在成为生物医学研究的一种基本的、可能是革命性的方法，有能力改进对各种疾病的预防、诊断和治疗，并促进个性化健康。本次会议旨在讨论生物库研究中的主要统计和定量挑战，包括满足广泛需求的生物库设计、提高表型准确性的策略、生物库之间的数据协调以及用于分析生物库数据的新的统计和数据科学方法。会议对整个研究界开放，特别鼓励初级教员和研究人员、博士后研究员、学生、妇女和代表性不足群体的成员参加。与会者将讨论和批评现有的量化方法，深入讨论新出现的统计和量化问题，并确定生物库数据设计和分析方面未来研究的优先事项。提交的研究成果将在科学期刊和网站的出版物中广泛传播。为了2018年PQG会议，我们召集了一个在生物库开发和研究设计方面经验丰富的跨学科演讲者团队，其中包括统计学家、医学信息学家、遗传学家、流行病学家和临床科学家。目前非常感兴趣的三个新出现的主题包括：种群生物库的设计；生物库的表型和协调；以及生物库数据分析。会议讨论将围绕1)不同类型生物库的实例，包括招募战略的不同实例、选择基因/技术、基因资源和未来方向、设计战略：横截面、纵向、有代表性的概率抽样以及增加多样性并扩展到美洲、非洲和亚洲；2)生物库的表型和协调问题，包括改进生物库内和跨生物库的表型协调的新方法、利用登记册数据丰富表型(事件的时间)、结合世界各地不同的生物库/登记册数据、偏向和缺失数据、电子健康记录中的错误分类以及电子健康记录数据库中的其他设计异质性问题；最后，与数据分析方法有关的问题，包括如何使分析具有计算可伸缩性，相关样本和混合样本的分析，多个表型和Phewas分析，丢失数据，表型错误分类，处理一些疾病的少量病例，风险预测，选择适当的对照，跨生物库的综合分析，以及不同数据类型(基因和表型，或转录和代谢组数据)的综合分析，或跨生物库复制表型。有关更多信息，请参阅https://www.hsph.harvard.edu/2018-pqg-conference/This奖项，该奖项反映了美国国家科学基金会的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。