GENOMIC INDEXING OF COMMON FUND DATASETS

共同基金数据集的基因组索引

• 批准号: 10907970
• 负责人: Aleksandar Milosavljevic
• 金额: $ 115.25万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-24 至 2024-09-23
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10907970
• 关键词: Acceleration; Address; Alleles; Area; Authorization documentation; Binding; Child; Chromatin; Clinical; Code; Collaborations; Communication; DNA Methylation; Data; Data Set; Environment; Funding; Genetic Transcription; Genomics; Genotype-Tissue Expression Project; Glean; Haplotypes; Individual; Internet; Letters; National Human Genome Research Institute; Participant; Phase; RNA; Regulatory Element; Research; Resources; System; Tissues; United States National Institutes of Health; Untranslated RNA; Validation; Variant; authority; clinical diagnostics; data modeling; data portal; design; epigenome; extracellular; genetic variant; genome resource; improved; indexing; infrastructure development; interoperability; multiple datasets; multiple omics; privacy protection; transcription factor

The accessibility of information relevant for interpreting genetic variants. As the pace of WGS accelerates, the interpretation of the 99% of variants revealed by WGS that are non-coding is of increasing importance. High-volume “omic” profiling datasets generated by Common Fund projects and derived information about specific variants and regulatory elements have great potential to inform the interpretation of such non-coding variants. NIH CF Roadmap Epigenome, GTEx and CF Extracellular RNA Communication Consortium (CF ERCC) already generate publicly shareable information about the impact of individual regulatory variants in the form of allele-specific DNA methylation, chromatin states, transcription factor binding, phased allelic transcription, e/sQTL information, and transcription status of non-coding and coding variants. More detailed information that may help evaluate functional effects of a variant in specific haplotype and tissue contexts can be gleaned from privacy-protected multi-omic profiles of biosamples containing the variant. Both the summary-level and the protected variant information is currently fragmented, poorly accessible and lacks interoperability. The scope of this project. By leveraging resources from the CF ERCC and NHGRI ClinGen projects (Table 1), we will unlock the value of variant information across Common Fund projects. One immediate aim will be to improve FAIRness of Extracellular RNA Communication Consortium (ERCC) data and make it accessible via the CFDE Data Portal. Additional two aims cut across CF projects and involve the development of infrastructure for “genomic indexing”, i.e., for aggregating variant information across CF projects and for making the information FAIR and useful in both the research and clinical use cases. The information will be aggregated at the summary-level that does not compromise identity of participants and also at the more detailed level that will be protected and will involve authorized access. We will initiate the cross-CF integration with variant information from Roadmap Epigenome, GTEx, and the Extracellular RNA Communication Consortium (ERCC) projects. In collaboration with GTEx (see letter from Dr. Kristin Ardlie, GTEx PI), we will make the aggregated variant information accessible via web UIs and APIs hosted at the CFDE Data Portal. The research and clinical diagnostic use cases. The research use cases will come from the NIH Common Fund Gabriella Miller Kids First-KOMP2 (see letters from Dr. Bruce Gelb, KidsFirst-KOMP2 PI, and Dr. Sharon Plon, KidsFirst PI). The clinical diagnostic use cases will come from the NHGRI Clinical Genome Resource (ClinGen) project (see letter from Dr. Sharon Plon, ClinGen PI). In collaboration with these projects, we will develop data models, data flows, system designs, and will participate in the validation of the systems. This collaboration between Drs. Gelb, Plon and Milosavljevic will build on several years of their previous collaboration within ClinGen where Dr. Gelb co-chairs the RASopathy Expert Panel and Drs. Plon and Milosavljevic serve on the ClinGen Steering Committee. FOA Areas addressed. As described below, our project will partner with CFDE-CC in the following two Areas listed in the FOA: Area 1 (Enabling access to, and computation across, multiple data sets in a cloud environment – addressed in this Section) and Area 3 (Enabling end-users to compute on data in the cloud – addressed in Section 2).

与解释遗传变异相关的信息的可访问性。随着WGS的步伐 加速，对 WGS 揭示的 99% 的非编码变异的解释是 越来越重要。由共同基金项目生成的大量“组学”分析数据集和 关于特定变体和调控元件的衍生信息具有巨大的潜力，可以为 此类非编码变体的解释。 NIH CF 路线图表观基因组、GTEx 和 CF 细胞外 RNA 通信联盟 (CF ERCC) 已经生成了有关 RNA 的可公开共享的信息 等位基因特异性 DNA 甲基化、染色质状态等形式的个体调控变异的影响， 转录因子结合、定相等位基因转录、e/sQTL 信息以及转录状态 非编码和编码变体。更详细的信息可能有助于评估功能效果 特定单倍型和组织环境中的变异可以从受隐私保护的多组学中收集 含有变体的生物样本的概况。摘要级别和受保护的变体 目前信息分散、访问困难且缺乏互操作性。 本项目的范围。经过 利用 CF ERCC 的资源 和 NHGRI ClinGen 项目（表 1）， 我们将解锁变体的价值 共同基金的信息 项目。近期目标之一是 提高细胞外RNA的公平性 通信联盟 (ERCC) 数据并使其可通过 CFDE 数据门户。另外两个目标 跨越 CF 项目并涉及 发展基础设施 “基因组索引”，即用于聚合 CF 项目的变体信息 并使信息在研究和临床用例中公平且有用。这 信息将在摘要级别进行汇总，不会损害参与者的身份，并且 也将在更详细的级别上受到保护并涉及授权访问。我们将发起 与来自 Roadmap Epigenome、GTEx 和 Extracellular 的变异信息进行跨 CF 整合 RNA 通信联盟 (ERCC) 项目。与 GTEx 合作（参见 Kristin 博士的来信 Ardlie，GTEx PI），我们将通过 Web UI 和 API 访问聚合的变体信息 托管在 CFDE 数据门户。 研究和临床诊断用例。研究用例将来自 NIH 共同基金 Gabriella Miller Kids First-KOMP2（请参阅 KidsFirst-KOMP2 PI Bruce Gelb 博士的来信， 和 Sharon Plon 博士，KidsFirst PI）。临床诊断用例将来自 NHGRI 临床 基因组资源 (ClinGen) 项目（参见 ClinGen PI Sharon Plon 博士的来信）。与合作 这些项目，我们将开发数据模型、数据流、系统设计，并将参与 系统的验证。博士之间的合作。盖尔布、普隆和米洛萨夫列维奇将在此基础上继续发展 他们之前在 ClinGen 合作多年，Gelb 博士担任 RASopathy 联合主席 专家小组和博士。 Plon 和 Milosavljevic 是 ClinGen 指导委员会的成员。 涉及的 FOA 领域。如下所述，我们的项目将在以下两个方面与CFDE-CC合作 FOA 中列出的领域： 领域 1（实现对多个数据集的访问和计算） 云环境——在本节中讨论）和区域 3（使最终用户能够计算云环境中的数据） 云——在第 2 节中讨论）。