Comprehensive reference map construction, geolocation and data integration for HuBMAP HIVE

HuBMAP HIVE 的综合参考地图构建、地理定位和数据集成

• 批准号: 9919986
• 负责人: John Carlo Marioni
• 金额: $ 60万
• 依托单位: NEW YORK GENOME CENTER
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-06-21 至 2020-06-20
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9919986
• 关键词: Algorithms; Anatomy; Atlases; Biological; Cells; Communities; Computer software; Computing Methodologies; Data; Data Set; Distributed Systems; Histologic; Human; Human body; Individual; Infrastructure; Maps; Measurement; Methods; Modality; Molecular; Organ; Positioning Attribute; Regulation; Resources; Structure; Supervision; System; Technology; Tissues; base; computer framework; data integration; design; flexibility; insight; novel; organizational structure; scaffold; tool

Abstract The healthy human body is composed of trillions of cells, whose molecular contents, spatial organization, interactions, and molecular contents are carefully regulated and precisely structured. While transformative advances in technology enable new types of anatomical, histological, spatial and single cell measurements, new methods for data integration are essential to discover commonalities across diverse human beings, and discover relationships between modalities across multiple scales. This requires novel computational frameworks, algorithms and scaled software. Here, we will leverage this unique opportunity to construct an integrated spatial and molecular map for the human body, by designing new methods to infer a Common Coordinate Framework (CCF) for both absolute positions and relative relationships, ‘geolocate’ new data points onto it, and enable querying and exploration from the biological community to derive new insights and hypotheses. We will (1) construct a CCF across multiple scales of human anatomy, a 3-d spatial representation of the human body with coordinate systems based on common features across individuals. To do this, we will develop a powerful suite of integration tools using a strategy based on ‘semi-supervised’ manifold alignment. (2) Develop analytical strategies to ‘geolocate’ new data onto this framework, thereby displaying the entirety of HuBMAP data on a conserved scaffold of human anatomy, suitable for both highly structured organs, distributed systems, and dynamical tissues; (3) Build infrastructure to allow users to flexibly explore and query this dataset, to identify relationships between molecular composition, tissue organization, and anatomical structure. Our MC will create an integrated atlas of a healthy human, representing a landmark public resource that will lead to transformative insights into the organization, interaction, and regulation of cells, tissues and organs across the human body.

摘要 健康的人体由数万亿个细胞组成，这些细胞的分子含量、空间组织、 相互作用和分子含量受到仔细的调控和精确的结构。虽然具有变革性 技术的进步使新型的解剖学、组织学、空间和单细胞测量成为可能，新的 数据集成的方法对于发现不同人类之间的共性以及发现 多个尺度上的医疗模式之间的关系。这需要新的计算框架， 算法和可扩展的软件。在这里，我们将利用这一独特的机会，构建一个完整的空间 和人体的分子图谱，通过设计新的方法来推断共同的坐标框架 (CCF)对于绝对位置和相对关系，将新数据点‘地理定位’到其上，并启用 来自生物界的质疑和探索，以得出新的见解和假设。我们将(1) 构建跨越多个人体解剖学尺度的CCF，即人体的三维空间表示 基于个人共同特征的坐标系。为此，我们将开发一款功能强大的套件 使用基于“半监督”流形对齐的策略的集成工具。(2)发展分析能力 将新数据‘地理定位’到此框架上的策略，从而在 人体解剖学的保守支架，适用于高度结构的器官、分布式系统和 动态组织；(3)建立基础设施，允许用户灵活地浏览和查询该数据集，以识别 分子组成、组织结构和解剖结构之间的关系。我们的主持人将创建 一个健康人的综合地图集，代表着一个里程碑式的公共资源，将导致变革 深入了解人体细胞、组织和器官的组织、相互作用和调节。