Data Analysis Core

数据分析核心

基本信息

  • 批准号:
    10211113
  • 负责人:
  • 金额:
    $ 13.55万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-09-14 至 2023-06-30
  • 项目状态:
    已结题

项目摘要

Three-dimensional (3D) representations of tissues can be readily understood by the human brain and are the most informative and accurate way to quantitatively and comprehensively study cellular state and its relationships in health and disease. To generate 3D tissue representations, molecular measurements at single cell resolution are needed. These measurements can be performed directly from intact tissue, or alternatively, serial sections of a tissue can be generated, measured and assembled into a 3D object. Equally important to data generation are powerful computational tools that enable first, integration of various data types with different resolutions into multiscale 3D tissue volumes; second, to identify single cells; and third, to derive meta-features from such 3D single cell tissue models. The computational tools employed and developed by the Data Analysis Core will not only enable such analyses of the lymphatic tissues, but will also be generally applicable to a wide range of molecular data types and tissues. Specifically, the Data Analysis Core will provide the infrastructure and computational tools to store the data and metadata, to integrate the different measurement modalities into multi-scale images, to generate 3D voxel representations of tissues, to identify the single cells in 3D representation, and to determine cell types, their neighborhood and other features. All of these analyses will be built on an open source computational pipeline (histoCAT), which was developed in the lab of Dr. Bodenmiller and is emerging as a standard analysis pipeline for highly multiplexed 2D and 3D tissue data of various types. The Data Analysis Core will use OME-tiff as a standard format for all data and metadata. Data will be stored in a flexible database (openBIS) that enables straightforward exchange of raw data, data at any step of processing, and the processing pipeline itself to the HIVE. The structure of data and metadata storage can be readily harmonized to the needs of the HIVE. Given that all molecular measurements in our proposal provide single cell resolved information, we will use the single cell as a “bucket” to integrate different imaging modalities. The images generated by the optical microscopy methods and by imaging mass cytometry will be segmented, and using cell labels and cellular and tissue features, the different data modalities will be integrated to generate multiscale, multiparamter images. The multiscale, serial 2D tissue maps will be registered to build the 3D voxel tissue models. A single cell resolved model will be generated using 3D segmentation approaches. Many algorithms will then be employed to derive meta-features, such as cell shapes, patterns of cellular neighborhoods, distances to morphological features, and tissue motifs. These meta-features can be visualized on the 3D model to support the study of biological phenomena. The proposed computational pipeline, together with the unprecedented datasets generated of the lymphatic organs within this project will provide highest quality and comprehensive 3D Atlas of the lymphatic organs and a scalable blueprint of data processing and visualization that can be readily employed for other data types and tissues.
组织的三维(3D)表示可以容易地被人脑理解,并且是组织的三维(3D)表示的基础。 最翔实和准确的方式来定量和全面研究细胞状态及其 健康和疾病的关系。为了生成3D组织表示,在单个位置处的分子测量是必要的。 需要细胞分辨率。这些测量可以直接从完整组织进行,或者, 可以生成、测量组织的连续切片并将其组装成3D对象。同样重要 数据生成是强大的计算工具,它首先能够将各种数据类型与 第一,将不同的分辨率转换成多尺度3D组织体积;第二,识别单细胞;第三, 从这样的3D单细胞组织模型的元特征。所使用和开发的计算工具, 数据分析核心将不仅能够对淋巴组织进行这种分析,而且还将通常 适用于广泛的分子数据类型和组织。具体而言,数据分析核心将 提供基础设施和计算工具来存储数据和元数据, 将测量模态转换为多尺度图像,以生成组织的3D体素表示, 3D表示中的单个细胞,并确定细胞类型,它们的邻域和其他特征。所有 这些分析将建立在一个开源计算管道(histoCAT)上,该管道是在 Bodenmiller博士的实验室,并正在成为高度多路复用的2D和3D组织的标准分析管道 各种类型的数据。数据分析核心将使用OME-tiff作为所有数据的标准格式, 元数据.数据将存储在一个灵活的数据库(openBIS)中,可以直接交换原始数据。 数据、任何处理步骤中的数据以及到HIVE的处理管道本身。数据结构和 元数据存储可以容易地与HIVE的需要相协调。假设所有的分子测量 在我们的建议中,提供单细胞解析信息,我们将使用单细胞作为"桶"来集成 不同的成像模式。通过光学显微镜方法和成像质量产生的图像 细胞计数将被分段,并使用细胞标记和细胞和组织特征,不同的数据 模态将被集成以生成多尺度、多参数图像。多尺度连续二维组织 图将被配准以构建3D体素组织模型。将生成单细胞解析模型 使用3D分割方法。然后将采用许多算法来推导元特征,例如 细胞形状、细胞邻域的模式、到形态特征的距离和组织基序。这些 元特征可以在3D模型上可视化,以支持生物现象的研究。拟议 计算管道,以及在此范围内产生的淋巴器官的前所未有的数据集, 该项目将提供最高质量和全面的淋巴器官3D图谱和可扩展的 数据处理和可视化的蓝图,可以很容易地用于其他数据类型和组织。

项目成果

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Bernd Bodenmiller的其他文献

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