GENOMIC INDEXING OF COMMON FUND DATASETS

共同基金数据集的基因组索引

• 批准号: 10683511
• 负责人: Aleksandar Milosavljevic
• 金额: $ 78.51万
• 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 2023-09-23
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10683511
• 关键词: Data Set; Funding; Genomics; Text; indexing

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).

解释遗传变异相关信息的可及性。随着WGS的步伐 加速，WGS揭示的99%的非编码变异的解释是 越来越重要。共同基金项目生成的大量“组学”概况数据集， 关于特定变体和调控元件的衍生信息具有很大的潜力， 这些非编码变体的解释。NIH CF Roadmap表观基因组、GTEx和CF细胞外 RNA通讯联盟（CF ERCC）已经生成了关于RNA通讯的公开共享信息。 等位基因特异性DNA甲基化，染色质状态， 转录因子结合，等位基因转录，e/sQTL信息，和转录状态， 非编码和编码变体。更详细的信息，可能有助于评估功能的影响， 在特定的单倍型和组织背景中的变异可以从受隐私保护的多组学分析中收集。 含有该变体的生物样品的图谱。摘要级和受保护的变量 目前信息支离破碎，难以获取，缺乏互操作性。 这个项目的范围。通过 利用CF ERCC的资源 和NHGRI ClinGen项目（表1）， 我们将释放变量的价值 共同基金信息 项目一个直接的目标将是 提高胞外RNA公平性 通信联盟（ERCC） 数据，并通过 CFDE数据门户。额外的两个目标 跨CF项目，并涉及 发展基础设施， “基因组索引”，即，用于聚集 跨CF项目的变量信息 并使信息公平和有用的研究和临床用例。的 信息将在摘要一级汇总，但不损害与会者的身份， 也是在更详细的级别上，其将受到保护并且将涉及授权访问。我们将启动 交叉CF整合来自Roadmap表观基因组、GTEx和细胞外 RNA通讯联盟（ERCC）。与GTEx合作（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 在CFDE数据门户网站托管。 研究和临床诊断用例。研究用例将来自NIH 共同基金加布里埃拉米勒儿童第一-KOMP 2（见信件博士布鲁斯盖尔布，儿童第一-KOMP 2 PI， 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（见Dr. Sharon Plon，ClinGen PI的信函）。协同 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。Gelb，Plon和Milosavljevic博士之间的合作将建立在 他们之前在ClinGen合作的几年中，Gelb博士共同主持了RASopathy 专家小组以及Plon和Milosavljevic博士担任ClinGen指导委员会成员。 FOA区域已解决。如下所述，我们的项目将与CFDE-CC在以下两个方面合作 FOA中列出的领域：领域1（允许访问和计算多个数据集， 云环境-在本节中讨论）和领域3（使最终用户能够计算 云-在第2节中解决）。