Data Analysis Center for Somatic Mosaicism Across Human Tissues Network

人体组织网络体细胞镶嵌数据分析中心

• 批准号: 10662721
• 负责人: Peter J Park
• 金额: $ 200万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10662721
• 关键词: Benchmarking; Bioinformatics; Biological Assay; Biological Process; Catalogs; Cell Fraction; ClinVar; Cloud Computing; Communities; Complex; Computer software; Computing Methodologies; Consult; Controlled Environment; Copy Number Polymorphism; DNA Insertion Elements; DNA Sequence Rearrangement; DNA Transposable Elements; Data; Data Analyses; Data Collection; Data Set; Databases; Detection; Development; Diploidy; Disease; Ensure; Environment; Funding; Genome; Genomics; Goals; Haplotypes; Health; Image; Individual; Ingestion; International; Intuition; Knowledge; Lead; Malignant Neoplasms; Measures; Metadata; Methods; Microsatellite Repeats; Mosaicism; Mutation; Population Heterogeneity; Positioning Attribute; Process; Protocols documentation; Quality Control; Regulation; Reproducibility; Research Personnel; Resources; Role; Sampling; Scheme; Scientist; Secure; Single Nucleotide Polymorphism; Software Engineering; Standardization; Technology; Testing; Tissue Procurements; Tissues; United States National Institutes of Health; Variant; Visual; Visualization; Visualization software; Work; archive data; bioinformatics tool; cloud platform; cohort; computational pipelines; data access; data analysis pipeline; data and analysis portal; data ecosystem; data management; data modeling; data portal; data sharing; data standards; data submission; data visualization; design; detection method; experience; flexibility; genome-wide; human tissue; improved; insertion/deletion mutation; large scale data; member; metadata standards; mosaic variant; novel strategies; single cell technology; tool; user-friendly; variant detection; web services

PROJECT SUMMARY The goal of the Somatic Mosaicism across Human Tissues (SMaHT) Network is to better characterize the occurrence of mosaic variants in human tissues and to understand their role in the regulation of biological processes that impact health and disease. The SMaHT Data Analysis Center (DAC) aims to collect and curate all data generated in the Network; assess, develop, and apply state-of-the-art analytical pipelines; and produce a variant catalog and a data portal for the scientific community. We have assembled a team of investigators, bioinformatics scientists, data curators, and software developers with a strong track record in mosaic variant analysis, long-read data analysis, data portal development, visualization, large-scale data management and computing, and development of secure and flexible cloud technologies. In Aim 1, we will work with the Network members to define data and metadata standards and ensure that high-quality data are generated, processed, and annotated uniformly and efficiently. In Aim 2, we will perform benchmark studies for the current tools and technologies for identification of mosaic variants and lead an effort to define and implement analytical pipelines on a cloud platform. We will also develop new approaches as needed. We will ensure that a comprehensive set of mosaic variants of all types (single nucleotide variants, indels, copy number variants, translocations, complex rearrangements, transposable element insertions, microsatellite mutations, repeat expansions, etc.) are identified, using short- and long-read platforms, genome-wide and targeted assays, and bulk and single cell technologies. In Aim 3, we will build a user-friendly and interactive data portal containing a variant catalog and featuring a read-level variant browser to enable the scientific community to fully utilize the Network data. We will ensure that all methods and processes are documented for full reproducibility and that all tools and data are freely available to the community. 1

项目概要 跨人体组织的体细胞镶嵌 (SMaHT) 网络的目标是更好地描述发生的情况 人体组织中的嵌合体变异并了解它们在调节生物过程中的作用 SMaHT 数据分析中心 (DAC) 旨在收集和整理生成的所有数据。 在网络中；评估、开发和应用最先进的分析管道并生成变体目录； 我们组建了一个由研究人员、生物信息学科学家组成的团队。 在马赛克变异分析、长读数据方面拥有良好记录的数据管理者和软件开发人员 分析、数据门户开发、可视化、大规模数据管理与计算、开发 在目标 1 中，我们将与网络成员合作定义数据和技术。 元数据标准，确保统一生成、处理和注释高质量的数据 在目标2中，我们将对当前的识别工具和技术进行基准研究。 我们将研究马赛克变体，并领导在云平台上定义和实施分析管道的工作。 我们还将根据需要开发新的方法，以确保所有类型的马赛克变体的全面设置。 （单核苷酸变异、插入缺失、拷贝数变异、易位、复杂重排、转座 使用短读和长读来识别元素、微卫星插入突变、重复扩展等） 在目标 3 中，我们将构建一个平台、全基因组和靶向测定以及批量和单细胞技术。 用户友好的交互式数据门户，包含变体目录并具有读取级变体浏览器 使科学界能够充分利用网络数据，我们将确保所有方法和流程。 已记录以确保完全可重复性，并且所有工具和数据均可免费提供给社区。 1