Data Management, Analysis, and Resources Dissemination Core

数据管理、分析和资源传播核心

• 批准号: 9919479
• 负责人: Christina A Cuomo
• 金额: $ 59.58万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9919479
• 关键词: Address; Bioinformatics; Biological; Biotechnology; Cells; Clinical Data; Cloud Computing; Communicable Diseases; Communities; Computer Analysis; Computer software; Computing Methodologies; Custom; Data; Data Analyses; Data Set; Data Storage and Retrieval; Development; Diagnosis; Documentation; Ensure; Funding; Generations; Genomic Centers for Infectious Diseases; Genomics; Goals; Human Resources; Hybrids; Individual; Infection; Infectious Diseases Research; Infrastructure; Institutes; Institutional Review Boards; Metadata; Metagenomics; Methods; Microbe; National Institute of Allergy and Infectious Disease; Parasites; Population; Process; Protocols documentation; Quality Control; Reagent; Recording of previous events; Research; Research Project Grants; Resources; Sampling; Scientist; Secure; Sequence Analysis; Software Engineering; Software Tools; System; Technology; Time; Training; Update; Variant; Viral; Virulence; Work; analytical tool; biodefense; bioinformatics resource; cluster computing; combat; computational pipelines; computer infrastructure; data management; data pipeline; data standards; data tools; diverse data; drug sensitivity; experience; flexibility; genomic data; improved; innovation; method development; new technology; novel; novel strategies; pathogen; prevent; programs; public repository; quality assurance; software infrastructure; tool; transmission process; transposon sequencing; vector

Data Management, Analysis, and Resources Dissemination Core summary The Broad Institute’s Genomic Center for Infectious Disease (GCID) will continue to apply its deep experience in large-scale genomic analysis to study the virulence, transmission, and drug sensitivity of pathogens as well as their critical interactions with hosts, vectors and other microbes. Achieving this will require combining data sets from diverse technologies with bioinformatics capabilities and computational analyses. The Broad GCID will draw on its expertise building and maintaining efficient computational processes and computational infrastructure to create a robust Data Management, Analysis, and Resources Dissemination Core. The Core will support our Research Projects with high-throughput sample tracking, metadata and data management, large-scale analysis, development of novel computational methods, and the rapid release of high quality data and associated resources. Our Data Core will harness the extensive technological capabilities of the Broad Institute and the vast experience of our personnel in genomic research to serve the ambitious goals of our Research Projects. The Core will also maintain a program of ongoing method development tied to innovations in the Technology Core and the goals of the Research Projects; these include methods for strain analysis in metagenomic samples, improved quality control analysis of sequence data, updating assembly methods to use long read- and hybrid-data, customized 10x Genomics data applications, analysis of horizontally transferred sequences, methods for Tn-Seq analysis, and training and evaluating new methods for variant calling. These methods are cross-cutting across our Research Projects and will be widely applicable to genomic infectious disease research. In addition to releasing data to public repositories, the Data Core will continue to move pipelines, processes, and data sets to the cloud, to accelerate the infectious research community’s access to our data and tools and enable others to reproduce our analyses.

数据管理、分析和资源传播核心摘要 布罗德研究所的传染病基因组中心（GCID）将继续应用其深厚的经验 在大规模的基因组分析中，研究病原体的毒力、传播和药物敏感性 因为它们与宿主、载体和其他微生物的重要相互作用。实现这一目标将需要结合数据 集合来自具有生物信息学能力和计算分析的不同技术。广泛的GCID 将利用其专业知识建立和维护高效的计算过程和计算 基础设施，以创建强大的数据管理，分析和资源传播核心。核心 将通过高通量样本跟踪、元数据和数据管理支持我们的研究项目， 大规模分析，开发新的计算方法，快速发布高质量数据 及相关资源。我们的数据核心将利用远大的广泛技术能力， 研究所和我们的工作人员在基因组研究方面的丰富经验，以服务于我们的宏伟目标。 研究项目。核心还将保持一个与创新相关的持续方法开发计划 在技术核心和研究项目的目标，其中包括应变分析方法， 宏基因组样本，改进序列数据的质量控制分析，更新使用的组装方法 长读取和混合数据，定制的10倍基因组数据应用程序，分析水平传输的 序列，Tn-Seq分析方法，以及训练和评估变异识别的新方法。这些 方法是贯穿我们的研究项目，并将广泛适用于基因组感染 疾病研究。除了将数据发布到公共存储库之外，数据核心还将继续移动 将管道、流程和数据集传输到云端，以加速传染病研究社区对 我们的数据和工具，并使其他人能够复制我们的分析。