III: Small: Novel Statistical Data Analysis Approaches for Mining Human Genetics Datasets

III：小型：挖掘人类遗传学数据集的新颖统计数据分析方法

• 批准号: 1715202
• 负责人: Petros Drineas
• 金额: $ 50万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1715202&HistoricalAwards=false
• 关键词: III; Small; Novel; Statistical; Data

The advent of modern genotyping and sequencing technologies has revolutionized human genetics research, allowing researchers to truly understand how different we are from one another. Large datasets describing the common patterns of human genetic variation may be easily thought of as matrices, with the rows representing individuals and the columns representing loci in the genome that correspond to common polymorphisms. The broader impact of such datasets cannot be overemphasized: they are a key resource for researchers to use to find genes affecting health, disease, and responses to drugs and environmental factors, as well as understanding the evolutionary and biological history of our species. Extracting useful information from such datasets promotes the progress of science and, at the same time, advances national health, prosperity and welfare. This project will bridge the gap between state-of-the-art algorithms for data analysis developed in the theoretical computer science and applied mathematics communities and the application of such algorithms to the analysis of the increasingly larger volume of datasets in the human genetics community.In the context of this project, first, from an algorithmic perspective, the project team will design and analyze novel algorithms for three prototypical, fundamental research topics that combine linear algebra and randomization, namely sparse Principal Components Analysis, matrix completion, and linear (or kernel) discriminant analysis. All three topics have been widely popular in the theoretical computer science, machine learning, and applied mathematics communities. Yet these research topics have been essentially overlooked by the population genetics community. Second, from a population genetics perspective, the team will apply the developed algorithms to gain novel insights regarding population structure, ancestry informative markers, and natural selection, as well as improve imputation methods and Genome-Wide Association Studies (GWAS) data analysis. All three methods will be evaluated on population genetics datasets that are available to the PIs. The project will train graduate students and will disseminate the results of the research to a broad community of applied mathematicians, theoretical computer scientists, and population geneticists.

现代基因分型和测序技术的出现使人类遗传学研究发生了革命性的变化，使研究人员能够真正了解我们彼此之间的差异。描述人类遗传变异常见模式的大数据集很容易被认为是矩阵，行代表个体，列代表基因组中与常见多态相对应的基因座。这样的数据集的更广泛的影响怎么强调都不为过：它们是研究人员用来寻找影响健康、疾病和对药物和环境因素的反应的基因的关键资源，以及理解我们物种的进化史和生物史。从这些数据集中提取有用的信息促进了科学的进步，同时促进了国家的健康、繁荣和福利。这个项目将在理论计算机科学和应用数学界开发的最先进的数据分析算法之间架起一座桥梁，并将这些算法应用于人类遗传学社区中日益增长的数据集的分析。在这个项目的背景下，首先，从算法的角度，项目团队将设计和分析三个结合了线性代数和随机化的典型基础研究课题的新算法，即稀疏主成分分析、矩阵完成和线性(或核)判别分析。所有这三个主题都在理论计算机科学、机器学习和应用数学社区中广泛流行。然而，这些研究主题基本上被种群遗传学社区忽视了。其次，从种群遗传学的角度来看，该团队将应用开发的算法来获得关于种群结构、祖先信息标记和自然选择的新见解，并改进归因方法和全基因组关联研究(GWAS)的数据分析。所有这三种方法都将在PI可用的群体遗传学数据集上进行评估。该项目将培训研究生，并将研究结果传播给广泛的应用数学家、理论计算机科学家和种群遗传学家社区。

项目成果

Genetic history of the population of Crete

克里特岛人口的遗传史

• DOI: 10.1111/ahg.12328
• 发表时间: 2019
• 期刊: Annals of Human Genetics
• 影响因子: 1.9
• 作者: Drineas, Petros;Tsetsos, Fotis;Plantinga, Anna;Lazaridis, Iosif;Yannaki, Evangelia;Razou, Anna;Kanaki, Katerina;Michalodimitrakis, Manolis;Perez‐Jimenez, Francisco;De Silvestro, Giustina
• 通讯作者: De Silvestro, Giustina

De Novo Sequence and Copy Number Variants Are Strongly Associated with Tourette Disorder and Implicate Cell Polarity in Pathogenesis.

从头序列和拷贝数变体与图雷氏障碍障碍密切相关，并暗示细胞极性在发病机理中。

• DOI: 10.1016/j.celrep.2018.08.082
• 发表时间: 2018-09-25
• 期刊: Cell reports
• 影响因子: 8.8
• 作者: Wang S;Mandell JD;Kumar Y;Sun N;Morris MT;Arbelaez J;Nasello C;Dong S;Duhn C;Zhao X;Yang Z;Padmanabhuni SS;Yu D;King RA;Dietrich A;Khalifa N;Dahl N;Huang AY;Neale BM;Coppola G;Mathews CA;Scharf JM;Tourette International Collaborative Genetics Study (TIC Genetics);Tourette Syndrome Genetics Southern and Eastern Europe Initiative (TSGENESEE);Tourette Association of America International Consortium for Genetics (TAAICG);Fernandez TV;Buxbaum JD;De Rubeis S;Grice DE;Xing J;Heiman GA;Tischfield JA;Paschou P;Willsey AJ;State MW
• 通讯作者: State MW

Genome-Wide Association Study Points to Novel Locus for Gilles de la Tourette Syndrome

• DOI: 10.1016/j.biopsych.2023.01.023
• 发表时间: 2024-06-24
• 期刊: BIOLOGICAL PSYCHIATRY
• 影响因子: 10.6
• 作者: Tsetsos，Fotis;Topaloudi，Apostolia;Paschou，Peristera
• 通讯作者: Paschou，Peristera

CluStrat: A Structure Informed Clustering Strategy for Population Stratification

CluStrat：用于人口分层的结构知情聚类策略

• DOI: 10.1007/978-3-030-45257-5_19
• 发表时间: 2020
• 期刊: Research in Computational Molecular Biology
• 作者: Bose, Aritra;Burch, Myson;Chowdhury, Agniva;Paschou, Peristera;Drineas, Petros
• 通讯作者: Drineas, Petros

Myasthenia gravis genome-wide association study implicates AGRN as a risk locus

• DOI: 10.1136/jmedgenet-2021-107953
• 发表时间: 2021-08
• 期刊: Journal of Medical Genetics
• 影响因子: 4
• 作者: Apostolia Topaloudi;Zoi Zagoriti;Alyssa C Flint;Melanie B. Martinez;Zhiyu Yang;Fotis Tsetsos;Y. Christou;George Lagoumintzis;E. Yannaki;E. Zamba-Papanicolaou;J. Tzartos;Xanthippi Tsekmekidou;K. Kotsa;E. Maltezos;N. Papanas;D. Papazoglou;P. Passadakis;Athanasios Roumeliotis;S. Roumeliotis;M. Theodoridis;E. Thodis;S. Panagoutsos;J. Yovos;J. Stamatoyannopoulos;K. Poulas;K. Kleopa;S. Tzartos;Marianthi Georgitsi;P. Paschou