Computational tools for uniform processing and integration of human reference atlas data [2 of 5]

用于统一处理和集成人类参考图集数据的计算工具 [2 of 5]

• 批准号: 10886347
• 负责人: Benedict Paten
• 金额: $ 90万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10886347
• 关键词: Anatomy; Atlases; Biological; Cells; Collaborations; Computational algorithm; Data; Data Display; Data Set; Development; Dimensions; Disparate; Ensure; Foundations; Friction; Human; Human BioMolecular Atlas Program; Image; Joints; Link; Maps; Methods; Modality; Phase; Process; Production; Provider; Public Health; Salmon; Standardization; Tissues; Work; cellular imaging; clinically relevant; computational pipelines; computerized data processing; computerized tools; differential expression; imaging Segmentation; indexing; innovation; insight; public health relevance; single-cell RNA sequencing; tissue mapping

The HuBMAP Computational Tools Component is responsible for development of standardized processing pipeline for all HuBMAP data, which is the foundation that enables joint storage, indexing, display, querying and mapping of HuBMAP datasets. A key innovative aspect that we have championed and, which as far as we know is unique for large consortia with several groups, platforms and data modalities is the fact that all HuBMAP pipelines we implemented provide uniform processing of all data from the same modality. Specifically, for each of these modalities we use the same computational algorithm for initial and downstream processing. For example, all scRNA-Seq datasets, regardless of which of the 7 platforms they were generated by, are processed by our Salmon quantification pipeline. This makes integration and comparison much easier across all HuBMAP data. In addition, all downstream analysis including dimensionality reduction, clustering, differential expression etc. are also performed using the same methods for all platforms making it easy to organize the display of the data on the portal and to index the data for quantitative queries. Similar pipelines have been developed for other modalities. In the production phase of the HuBMAP Consortium, we will extend these computational pipelines to support additional data types from new tissue mapping centers and other data providers. We will additionally extend our focus beyond single-cell image segmentation to support the mapping efforts of the Human Reference Atlas (HRA) collaboration, producing hierarchical links from cells to functional tissue units to higher-level anatomical structures.

HuBMAP计算工具组件负责开发标准化的 所有HuBMAP数据的处理管道，这是实现联合存储，索引， HuBMAP数据集的显示、查询和映射。我们一直倡导的一个关键创新方面 据我们所知，这对于拥有多个集团、平台和数据的大型财团来说是独一无二的。 我们实现的所有HuBMAP管道都提供了对所有数据的统一处理 从相同的模式。具体而言，对于这些模态中的每一种，我们使用相同的计算 初始和下游处理的算法。例如，所有scRNA-Seq数据集，无论 它们是由7个平台中的哪一个生成的，由我们的Salmon量化管道处理。 这使得所有HuBMAP数据的集成和比较更加容易。酒店客房经过精心 下游分析包括降维、聚类、差分表达等， 所有平台都使用相同的方法执行，从而易于组织数据的显示 并为数据编制索引以进行定量查询。类似的管道已经开发， 其他方式。 在HuBMAP联盟的生产阶段，我们将扩展这些计算管道， 支持来自新组织绘图中心和其他数据提供商的其他数据类型。我们将 此外，我们还将关注点扩展到单细胞图像分割之外，以支持 人类参考图谱（HRA）协作，产生从细胞到功能的层次链接 组织单位到更高层次的解剖结构。