An Integrative Analysis of Structural Variation for the 1000 Genomes Project

千人基因组计划结构变异的综合分析

• 批准号: 8589933
• 负责人: CHARLES LEE
• 金额: $ 276.6万
• 依托单位: JACKSON LABORATORY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-20 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8589933
• 关键词: Accounting; Algorithms; Alleles; Benchmarking; Biology; Chromosomes; Complement; Complex; Consensus; DNA; DNA Insertion Elements; Data; Demography; Detection; Development; Future; Gene Conversion; Genetic Variation; Genome; Genotype; Goals; Gold; Haplotypes; Health; Hereditary Disease; Human; Human Genetics; Machine Learning; Maps; Methods; Modeling; Nucleotides; Phase; Population; Process; Reading; Repetitive Sequence; Research; Resolution; Resources; Sampling; Site; Statistical Models; Technology; Validation; Variant; base; design; genetic variant; genome sequencing; improved; method development; novel; research study; tool

DESCRIPTION (provided by applicant): Structural variation (SV), involving deletions, duplications, insertions and inversions of DNA segments, accounts for a large proportion of human genetic diversity. Comprehensive identification and analysis of these genetic variants will help us more fully elucidate the biology of their functional effects on human health and demography. Despite recent advances, the tools and data needed to comprehensively identify all types of SVs, genotype each variant, integrate and phase these variants remain lacking. Indeed, the data released from the early phases of the 1000 Genomes Project (1000GP) (1000 Genomes Project Consortium, 2010; 1000 Genomes Project Consortium, 2012) are biased primarily towards the detection of deletions within relatively unique regions of the genome. As a consortium, we propose to pool expertise from various research groups to provide an integrative analysis of SVs by combining rigorous computational algorithmic development with extensive experimental validation. The new algorithms we develop and the high confidence lists of SVs obtained will be rapidly made available as a public resource.

描述（申请人提供）：结构变异（SV），涉及DNA片段的缺失、重复、插入和倒位，占人类遗传多样性的很大比例。对这些遗传变异的全面鉴定和分析将有助于我们更全面地阐明它们对人类健康和人口统计学的功能性影响的生物学。尽管最近取得了进展，但仍然缺乏全面识别所有类型的SV、对每个变体进行基因分型、整合和分阶段这些变体所需的工具和数据。事实上，从1000个基因组计划（1000 GP）（1000个基因组计划联盟，2010; 1000个基因组计划联盟，2012）的早期阶段发布的数据主要偏向于检测基因组相对独特区域内的缺失。作为一个财团，我们建议汇集来自不同研究小组的专业知识，通过将严格的计算算法开发与广泛的实验验证相结合，提供对SV的综合分析。我们开发的新算法和获得的SV的高置信度列表将作为公共资源迅速提供。