Computational methods for large-scale genotype data

大规模基因型数据的计算方法

• 批准号: 10409820
• 负责人: BRIAN LEE BROWNING
• 金额: $ 45万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10409820
• 关键词: Address; Alleles; Chromosomes; Code; Computer software; Computing Methodologies; Data; Data Set; Diagnosis; Diploidy; Disease; Genetic; Genetic study; Genotype; Growth; Haplotypes; Heritability; Individual; Inherited; Libraries; Methodology; Methods; Modeling; New Acceptors; Parents; Performance; Phase; Population; Prevention; Research; Research Personnel; Sample Size; Sampling; Scientist; Time; United States; Update; X Chromosome; autosome; cohort; cost; disorder risk; file format; genetic pedigree; genetic variant; improved; large datasets; male; offspring

Project Summary The size of genetic data sets is growing exponentially. At the current rate of growth, the largest reference panels of phased, sequenced individuals will have millions of individuals within 5-7 years. This research will address the computational challenges of performing genotype phasing and imputation in large cohorts and with large reference panels. Large cohorts from outbred populations typically contain a mixture of nominally unrelated and closely related individuals. Current phasing methods for these large data sets do not model parent-offspring or other close relationships. We will develop a new phasing method that greatly increases phase accuracy in closely-related individuals and that scales to large sample sizes. Increasing reference panel size also increases genotype phase and imputation accuracy. However, computational cost also increases with reference panel size. We will develop a new reference file format that substantially reduces the computational cost of imputation and phasing with large reference panels. We will provide a format specification, software, and software libraries so that other researchers and software developers can readily use the new reference file format. We will develop a new computational method for finding shared haplotype segments between a reference panel and a target haplotype. This new method will significantly reduce the cost of phasing and imputation using large reference panels. Finally, we will extend the fastest, most accurate method for genotype phasing and imputation (Beagle 5.0) to analyse chromosome X data. This extension will improve genetic studies of this important chromosome.

项目摘要 基因数据集的规模呈指数级增长。按照目前的增长速度， 在5-7年内，定相的、测序的个体的参考组将具有数百万个个体。这 研究将解决基因型定相和插补的计算挑战， 大型队列和大型参考面板。 来自远交群体的大群体通常包含名义上无关和密切相关的混合物。 相关的个人。目前用于这些大型数据集的定相方法并不对亲代-子代或子代进行建模。 其他亲密关系。我们将开发一种新的定相方法，大大提高相位精度 在密切相关的个人和规模，以大样本量。 增加参考样本组的大小也会增加基因型相位和插补准确度。然而，在这方面， 计算成本也随着参考面板尺寸而增加。我们将开发一种新的参考文件格式 这大大降低了估算和定相的计算成本， 板.我们将提供格式规范、软件和软件库，以便其他研究人员 并且软件开发者可以容易地使用新的参考文件格式。 我们将开发一种新的计算方法，用于寻找不同基因型之间共享的单倍型片段。 参考组和目标单倍型。这种新方法将大大降低分阶段的成本 并使用大型参考面板进行插补。 最后，我们将扩展用于基因型定相和插补的最快、最准确的方法（Beagle 5.0)来分析X染色体数据这一扩展将改善这一重要的遗传学研究。 染色体

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

Genetics of the peloponnesean populations and the theory of extinction of the medieval peloponnesean Greeks.

• DOI: 10.1038/ejhg.2017.18
• 发表时间: 2017-05
• 期刊: European journal of human genetics : EJHG
• 作者: Stamatoyannopoulos G;Bose A;Teodosiadis A;Tsetsos F;Plantinga A;Psatha N;Zogas N;Yannaki E;Zalloua P;Kidd KK;Browning BL;Stamatoyannopoulos J;Paschou P;Drineas P
• 通讯作者: Drineas P