Data Processing, Analysis and Modeling Unit

数据处理、分析和建模单元

• 批准号: 10005918
• 负责人: Jeremy Goecks
• 金额: $ 67.21万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-19 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10005918
• 关键词: 3-Dimensional; ATAC-seq; Aftercare; Atlases; Biological; Biological Assay; Biological Process; Biopsy; CDK4 gene; Cancer Patient; Cells; Characteristics; Communities; Computer software; Data; Data Analyses; Data Management Resources; Data Storage and Retrieval; Disseminated Malignant Neoplasm; Electron Microscopy; Generations; Genes; Goals; Image; Image Analysis; Immune; Immune checkpoint inhibitor; Immunofluorescence Immunologic; Immunohistochemistry; Immunomodulators; Individual; Infiltration; Malignant Neoplasms; Malignant neoplasm of prostate; Maps; Measurement; Metastatic breast cancer; Methods; Modeling; Mutation; Neoplasm Metastasis; Pathway interactions; Patients; Periodicity; Population; Primary Neoplasm; Reproducibility; Research; Resistance; Resistance development; Running; Sampling; Services; Standardization; Statistical Data Interpretation; Structure; System; Techniques; Time; Tissues; Visualization; Visualization software; animation; base; blood vessel development; castration resistant prostate cancer; cohort; computerized data processing; dashboard; data management; epigenomics; hormone receptor-positive; hormone therapy; immune checkpoint; indexing; individual patient; inhibitor/antagonist; malignant breast neoplasm; molecular imaging; molecular targeted therapies; multimodal data; multimodality; novel; prospective; resistance mechanism; single cell sequencing; statistical and machine learning; targeted treatment; therapy resistant; triple-negative invasive breast carcinoma; tumor

ABSTRACT – Data Analysis Unit We propose to create a Data Analysis Unit in service of the Omics and Multidimensional Spatial (OMS) Atlas. The OMS Atlas will enable discovery of mechanisms of resistance that arise in individual patients with metastatic breast and prostate cancer during treatment with current generation of targeted therapeutic combinations and immune checkpoint inhibitors. Treatment will these therapies in metastatic cancer is rarely effective for an extended period of time, and understanding the mechanisms by which these cancers become resistant to therapy is the primary goal of the OMS Atlas. The Data Analysis Unit will support this goal by developing and deploying data management, processing, analysis, and visualization methods and software to create the Atlas. The OMS Atlas will collect two biopsies, one before treatment and one during treatment for 3 different cohorts of cancer patients. The final product of the Data Analysis Unit will be a complete tumor atlas accessible via an interactive portal that enables use-case biologists in the OMS Atlas, the HTAN and the larger research community to develop hypotheses about tumor resistance mechanisms through quantified, longitudinal, and spatially-resolved comparisons of pre- and on/post-treatment biopsies from individual patients. Using primary data generated from omics and imaging assays (Tier 1 data), the Data Analysis Unit will generate three additional tiers of data: (Tier 2) single gene/cell measurements obtained by processing data from a single data platform; (Tier 3) tumor maps generated by combining single-cell and spatially-resolved omics and imaging data as well as quantification of systems-level functions such as biological pathway activity and the cells comprising the tumor and its surrounding tissue using integrative analyses of multiple data platforms; (Tier 4) a tumor atlas that can be used to compare pre- and on/post-treatment biopsies and identify features potentially correlated with resistance to treatment. Data tiers will be generated using a robust software pipeline consisting of a data management system, image management software, a workflow execution system, and visualization tools. Standardized and reproducible workflows that run on this platform will be implemented to generate all tiers of data. Statistical and machine learning approaches will be used to create tumor maps by connecting mirror image sections and cell populations across different assays. The OMS Atlas portal will provide a single interface with access to 10 different visualizations of tumor maps. Tumor maps can be visualized and compared longitudinally within a single patient or laterally across patients. Many visualizations can be displayed simultaneously using a dashboard approach where visualizations can be progressively added as desired, making it possible to view many different types of data about tumor maps simultaneously. Specialized animation approaches and 3D techniques will be used in visualizations to effectively display multidimensional, spatially resolved tumor map data.

摘要 - 数据分析单元 我们建议创建一个数据分析单元，以服务OMICS和多种多样的空间（OMS）地图集。 OMS地图集将能够发现在患有的个别患者中出现的抗药性机制 靶向治疗的电流治疗期间转移性乳腺癌和前列腺癌 组合和免疫检查点抑制剂。 在很长一段时间内有效，并了解这些癌症成为的机制 对治疗的抵抗力是OMS地图集的主要目标。 开发和部署数据管理，处理，分析，可视化方法和软件。 创建Atlas。 癌症患者的不同人群。 可以通过交互式门户访问Thital Thital可以在OMS ATLA，HTAN和较大的OMS Atlas中使用用例生物学家 研究社区通过量化的，关于肿瘤抗性机制的假设 纵向和空间排序 使用OMICS和Imaging测定法产生的主要数据（数据分析单元） 将生成三个额外的数据：（第2层）通过处理数据获得的单基因/细胞测量值 来自一个数据平台； OMICS和成像数据以及系统级功能（例如生物学途径活动）的量化 以及使用肛门肛门数据包含组织周围肿瘤ATS的细胞 平台； 特征可能与对治疗的抗性有关。 管道由数据管理系统，图像管理软件，工作流执行系统组成， 和可视化工具。 为了生成所有数据层。 在不同测定中连接镜像部分和单元格。 提供单个界面，可访问10个不同的肿瘤图。 在单个患者或横向的患者中进行可视化和纵向比较 可以使用仪表板方法同时显示可视化的仪表板方法 根据需要，可以同时查看有关肿瘤图的许多不同类型的数据。 专门的动画方法和3D 3D技术将用于可视化以进行有效显示。 多维的，空间分辨率的肿瘤图数据。