Tool for annotation and analyses of human whole-genome sequence variation data

人类全基因组序列变异数据注释和分析工具

• 批准号: 7943988
• 负责人: MARTIN G REESE
• 金额: $ 38.47万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7943988
• 关键词: Adopted; Biology; Biomedical Research; Cell Line; Cells; Code; Collection; Communities; Computer software; Computers; Consent; DNA Sequence; Data; Data Analyses; Data Quality; Data Set; Databases; Deposition; Development; Diagnostic; Disease; Functional RNA; Funding; Future; Generations; Genes; Genome; Genomics; Grant; Human Genetics; Human Genome; Human Genome Project; Individual; Informatics; Inherited; Internet; Knowledge; Letters; Methods; Normal tissue morphology; Online Mendelian Inheritance In Man; Ontology; Positioning Attribute; Predisposition; Primary Neoplasm; Privacy; Procedures; Process; Research; Research Personnel; Resources; Running; Scientist; Sequence Alignment; Software Tools; Solutions; Sorting - Cell Movement; System; Technology; Tumor Tissue; Variant; abstracting; cancer genome; chemical function; comparative genomics; design; genome sequencing; genome wide association study; genome-wide; information highway; meetings; neoplastic cell; operation; prognostic; response; software development; success; tool; trait; tumor

DESCRIPTION (provided by applicant): Abstract Current estimates place the number of personal variants at approximately 4 million per genome. Given the rapid advances in genome sequencing technologies and the future democratization of human genome sequencing, small groups and even individual scientists will soon be performing their own human genome projects. We believe that the ability to automatically annotate the millions of variants that these projects will produce, to combine data from multiple projects, and to recover subsets of annotated variants for diverse downstream analyses will become a critical analysis bottleneck. Despite the need, there are no publically available tools that automate these procedures. In response to the NHGRI's RFA "Development and Application of Statistical and Computational Data Analysis Methods for DNA Sequence, Variation, GWAS, Genomic Function, Chemical Biology and Related Genomic Data Sets" we propose in this GO grant to develop a standalone software tool called VAAST-Variant Annotation, Analysis and Selection Tool. This system will fulfill NHGRI's need for a technology to assess data quality and call variants and will allow for analysis of data from all sequencing centers and will be useable for data from all sequencing platforms. We believe VAAST will fill a huge void in the software landscape by helping individual scientists to extract meaningful results from whole genome variant files. PUBLIC HEALTH RELEVANCE: It is now known that on average any two individual human genomes differ by approximately 4 million positions. These differences, called sequence variants, underlie the inherited physical differences between individuals, including their predisposition to develop certain diseases. This project proposes to develop a tool called VAAST- Variation Annotation, Analysis and Selection Tool. VAAST will help researchers sort through these millions of variants in their quest to identify which of them underlie different phenotypic traits of individuals and susceptibility to diseases.

描述（申请人提供）：抽象当前估计值将个人变体数量的每个基因组约为400万。鉴于基因组测序技术的快速进步以及人类基因组测序的未来民主化，小组甚至个人科学家很快将执行自己的人类基因组项目。我们认为，自动注释这些项目将产生的数百万变体，结合多个项目的数据，并恢复带注释的变体的子集以进行多种下游分析的子集的能力将成为一个关键的分析瓶颈。尽管有需要，但仍未公开可自动化这些过程的工具。响应NHGRI的RFA“开发和应用DNA序列，变化，GWAS，基因组功能，化学生物学和相关基因组数据集的统计和计算数据分析方法”“我们在此GO Grant中提出了一个独立的软件工具，以开发一种称为VAAST-VARIANT-VARIANT-VAR-VAR-VAR-VAR-VAR-VAR-VARIANT-VAR-ANTORIANT-ANTORTAINT，分析，分析和选择工具。该系统将满足NHGRI对评估数据质量和调用变体的技术的需求，并允许对所有测序中心的数据进行分析，并且可用于所有测序平台的数据。我们认为，Vaast通过帮助各个科学家从整个基因组变体文件中提取有意义的结果来填补软件景观中的巨大空隙。 公共卫生相关性：现在众所周知，任何两个人的人类基因组平均差异约为400万个职位。这些差异（称为序列变体）是个体之间遗传的物理差异的基础，包括它们发展某些疾病的倾向。该项目建议开发一种称为Vaast-变化注释，分析和选择工具的工具。 VAAST将帮助研究人员对这些数百万变体进行分类，以确定其中哪些是个人的不同表型特征和对疾病的易感性的基础。