GENOMIC INDEXING OF COMMON FUND DATASETS

共同基金数据集的基因组索引

• 批准号: 10223726
• 负责人: Aleksandar Milosavljevic
• 金额: $ 31.63万
• 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/10223726
• 关键词: Address; Alleles; Area; Binding; 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; Privacy; RNA; Regulatory Element; Research; Resources; System; Tissues; United States National Institutes of Health; Untranslated RNA; Validation; Variant; clinical diagnostics; data modeling; data portal; design; epigenome; extracellular; genetic variant; genome resource; improved; indexing; infrastructure development; interoperability; multiple datasets; multiple omics; 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获得性。随着WGS的步伐 加速，对WGS揭示的99%非编码变体的解释是 变得越来越重要。共同基金项目和共同基金项目生成的大量“经济”概况数据集 关于特定变体和调控元件的派生信息具有很大的潜力，可以为 对这种非编码变体的解释。NIH CF路线图表观基因组、GTEx和CF胞外 RNA通信联盟(CF ERCC)已经生成了可公开共享的关于 以等位基因特异性DNA甲基化、染色质状态、 转录因子结合、阶段等位基因转录、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 特定单倍型和组织背景的变异可以从隐私保护的多组分中收集 含有变异体的生物样本的图谱。摘要级别和受保护的变体 信息目前支离破碎，难以获取，缺乏互操作性。 这个项目的范围。通过 利用来自CF ERCC的资源 和NHGRI Clingen项目(表1)， 我们将解锁变量的值 共同基金中的信息 项目。一个直接的目标将是 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 切入CF项目，并让 基础设施的发展 “基因组索引”，即用于聚合 跨CF项目的不同信息 并使信息在研究和临床使用案例中公平和有用。这个 信息将在不损害参与者身份的摘要级别进行汇总，并 也是在更详细的层面上，这将受到保护，并将涉及授权访问。我们将启动 与来自Roadmap epigenome、GTEx和细胞外的各种信息的交叉CF集成 RNA通信联盟(ERCC)项目。与GTEx合作(见克里斯汀博士的信 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数据门户上。 研究和临床诊断使用案例。研究用例将来自美国国立卫生研究院 共同基金Gabriella Miller Kids First-KOMP2(见Bruce Gelb博士的信，KidsFirst-KOMP2 Pi， 和莎伦·普隆博士，儿童第一少年派)。临床诊断用例将来自NHGRI临床 基因组资源(Clingen)计划(见Sharon Plon博士的信，Clingen Pi)。与 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博士、Plon博士和Milosavljevic博士之间的合作将建立在 他们之前在克林根进行了几年的合作，盖尔布博士在那里共同主持了Rasopsis 专家小组以及Plon博士和Milosavljevic博士在Clingen指导委员会任职。 解决了FOA领域的问题。如下所述，我们的项目将在以下两个方面与CFDE-CC合作 FOA中列出的区域：区域1(允许访问和跨多个数据集 云环境-在本节中介绍)和区域3(使最终用户能够计算 第2节中的云寻址)。