Software for the analysis of large-scale genotyping and sequencing studies

描述(由申请人提供)：该项目的目标是在现有软件包Plink的基础上，开发用于分析大规模基因分型和基因测序研究的数据的软件。Plink是一种操作和分析全基因组SNP数据集的软件工具，在过去四年中一直在积极开发，拥有广泛的用户基础。具体目标是大幅提升核心能力、接口、辅助资源和用户支助：核心能力：大幅调整和升级数据存储能力，以处理a)比内存容量大数量级的数据集和b)更通用、更统一的不同类型遗传变异数据和元信息的表示。接口：扩展现有接口，以便a)通过外部语言的多个接口，包括R和Perl等标准生物信息学工具，在数据存储和分析组件之间提供更松散的耦合，以及b)旨在促进可重复研究和并行处理的功能。辅助资源：打包标准的现有资源，包括变异、参考基因组序列和基因组合、途径和本体论的功能注释，以允许基因组资源和用户数据之间的无缝整合。支持：通过在线文档和教程，包括用户生成的维基页面、电子邮件支持和年度培训课程，创建高质量的收藏资源来支持用户。将特别注意确保与更广泛的遗传学社区产生的其他主要软件、文件格式和资源的互操作性。 公共卫生相关性：该项目旨在开发用于分析现代基因研究中的大数据集的软件。新的高通量基因分型和测序技术能够产生海量数据，但需要生物医学研究人员可以使用的分析工具。这些研究有可能揭示大量疾病和特征的遗传决定因素，这些决定因素可能与风险预测相关，并为治疗提供新的靶点。

DESCRIPTION (provided by applicant): The objective of this project is to develop software for the analysis of data from large- scale genotyping and sequencing genetic studies, building on the existing software package PLINK. PLINK, a software tool to manipulate and analyze whole-genome SNP datasets that has been actively developed over the past four years and has a wide base of users. The specific aims are to significantly upgrade core capacities, the interface, auxiliary resources and user-support: Core capacities: significantly adapt and upgrade data-storage capacities to handle a) order-of-magnitude larger datasets than can fit into memory and b) a more generic, unified representation of different types of genetic variation data and meta-information. Interface: extend the existing interface to provide a) a looser coupling between data storage and analysis components, via multiple interfaces in external languages, including standard bioinformatics tools such as R and Perl, and b) features designed to facilitate reproducible research and parallel processing. Auxiliary resources: package standard existing resources, including the functional annotation of variants, reference genome sequences and gene assemblies, pathways and ontologies, in a manner that allows seamless integration between genomic resources and user data. Support: create high-quality collection resources to support users, via online documentation and tutorials, including user-generated wiki pages, e-mail support and an annual training course. Particular attention will be paid to ensure interoperability with other major software, file-formats and resources that are generated by the broader genetics community. PUBLIC HEALTH RELEVANCE: This Project is to develop software for the analysis of large datasets from modern genetic studies. New high-throughput genotyping and sequencing technologies are capable of producing vast amounts of data, but there is a need for analytic tools that biomedical researchers can use. These studies have the potential to uncover genetic determinants for a large number of diseases and traits, which can be relevant for prediction of risk, and give insight into novel targets for treatments.