Bridging dataset generation to enable integrated data analysis and interpretation across HuBMAP tissues

项目总结 本补充的目标是生成所有HuBMAP组织的桥接数据集，以允许HuBMAP 聚合和集成来自每个组织的关于解剖的数据和元数据的联盟 以标准化方式提供参考资料，以便利数据整合、分析和解释。我们将表演 10x基因组铬单细胞多重体ATAC+基因在冻存组织中的表达分析 跨多个组织映射中心(TMC)的每个器官的样本。该检测方法能够收集RNAseq 和ATACseq数据，这些数据在单细胞/单核水平上相连。我们将把单个组织连接到10倍 将多组桥数据集连接到每个解剖、结构、细胞类型和生物标志物(ASCT+B)表 每个器官建立一个框架，以输入到HuBMAP蜂箱的注册用户界面。我们将确保 这些数据(用详细的生物和技术元数据作注释)将被广泛使用， 不仅包括建立3D多比例尺地图，这是该联盟的主要目标，而且还 开发用于分析和集成的新的剖面技术和计算方法 跨多种组织类型的多种数据类型。我们将迅速将这些桥梁数据集发布给TMC，以便 与特定于器官的TMC空间数据集成，以构建由此导出的空间分辨率3D组织图 公共桥接数据集。作为HuBMAP综合数据分析和解释工作的联合主席 小组并通过参与合作项目和出版物工作组规划 跨组织综合数据分析手稿，我们发现了HuBMAP联合体中的这一重要缺口 目前已生成或计划在HuBMAP 2022年会上生成的数据集。正在生成一个 跨越所有HuBMAP组织的桥接数据集将为所有单独的器官图谱创建锚，并启用 跨联盟数据集的综合分析，以评估组织间细胞计数的相似性和差异性 组成，细胞类型和状态，邻里和功能单位。

PROJECT SUMMARY The goal of this supplement is to generate bridging datasets across all HuBMAP tissues to allow the HuBMAP Consortium to aggregate and integrate data and metadata from each tissue with respect to anatomical references in a standardized manner to facilitate data integration, analysis and interpretation. We will perform the 10x Genomics Chromium Single Cell Multiome ATAC + Gene Expression assay on snap- frozen tissue samples for each organ across several Tissue Mapping Centers (TMC). This assay enables collection of RNAseq and ATACseq data that are linked at the single-cell/single-nucleus level. We will link the individual tissue 10x Multiome bridge datasets to each of the Anatomic, Structural, Cell Types and Biomarkers (ASCT+B) tables for each organ to build a framework to input into the HuBMAP HIVE’s Registration User Interface. We will ensure that these data (annotated with detailed biological and technical metadata) will be made available for broad use, including not only the building of 3D multiscale maps that are the primary goal of this Consortium, but also development of novel profiling technologies and computational approaches for analysis and integration of multiple data types across multiple tissue types. We will rapidly release these bridge datasets to the TMCs to be integrated with the organ-specific TMC spatial data to build spatially-resolved 3D tissue maps derived from this common bridging dataset. As the Co-Chair of the HuBMAP Integrated Data Analysis & Interpretation Working Group and through involvement with the Collaborative Projects and Publications Working Group planning the cross-tissue integrative data analysis manuscript, we identified this important gap in the HuBMAP Consortium datasets currently generated or planned to be generated at the HuBMAP 2022 Annual Meeting. Generating a bridging dataset across all HuBMAP tissues will create an anchor for all individual organ atlases and enable integrative analysis across consortium datasets to assess similarities and differences across tissues in cell count composition, cell types and states, neighborhoods and functional units.