Multi-Scale Multi-Modality High Resolution Mapping of the Adult Human Lung

项目摘要/摘要 数据分析核心 多模式高分辨率人体肺部三维图谱的合成 数据分析核心(DAC)负责数据和元数据管理、处理、 该组织测绘中心(TMC)和器官特定项目的分析、测绘和共享 在成人健康人肺上(即肺特异性项目或LSP)。我们将从长远的角度看待地图集，作为 2D和3D地图的集合，其中包含图像、表格数据、关于不同分辨率的多个位置的事实 和命名对象的索引，这些对象以类似于纬度和经度的位置网格的坐标为关键字，以 以地图的方式呈现了人类肺部的所有显著特征。DAC将支持TMC 在这些活动中，通过为数据存储和计算提供受保护的环境以及通过开发 强大的可复制、可重复使用和可扩展的计算工作流，从而实现数据类型的集成 转换成3D地图，以创建交互式和可查询的生物分子人类图谱。DAC是一种 TMC的重要组成部分，其目标是生产和向母公司交付广泛的高分辨率集合 分子实体的空间映射，使用开放格式，并在细胞和细胞外的背景下 肺的组织。发援会将通过以下具体目标完成其作用：1)摄取和 处理TMC数据集，2)分析数据集以支持生成多尺度、多参数的肺组织 地图、表格数据和注释，3)构建具有集成数据集的2D和3D肺组织地图和4) 与HuBMAP联盟协调规划和地图集制作。

Project Summary/Abstract Data Analysis Core Synthesis of the Multimodality High Resolution 3-D Atlas of Human Lung The Data Analysis Core (DAC) is responsible for all aspects of data and metadata management, processing, analysis, mapping, and sharing for this Tissue Mapping Center (TMC) and of the Organ Specific Project focused on the adult healthy human lung (i.e., Lung Specific Project or LSP). We will take a long view of an Atlas, as a collection of 2D and 3D maps containing images, tabular data, facts about multiple locations at varying resolution and indexes of named objects keyed to coordinates of a locational grid analogous to latitude and longitude, to cartographically present the whole range of salient features of the human Lung. The DAC will support the TMC in these activities by providing a protected environment for data storage and computation, and by developing robust reproducible, reusable, and scalable computational workflows thus enabling the integration of data types into 3D maps for the purpose of creating an interactive and queryable biomolecular human atlas. The DAC is an essential part of the TMC in its objectives to produce and deliver to the HIVE extensive sets of high-resolution spatial mappings of molecular entities, using open formats, and within the context of the cellular and extracellular organization of the Lung. The DAC will accomplish its role through the following Specific Aims: 1) Ingest and process TMC datasets, 2) Analyze datasets in support of generating multiscale, multiparameter lung tissue maps, tabular data, and annotations, 3) Construct 2D and 3D lung tissue maps with integrated datasets and 4) Coordinate planning and atlas production with the HuBMAP Consortium.