Enhance UCSC Xena: extend interactive visualization to ultra-large-scale multi-omics data and integrate with analysis resources

增强 UCSC Xena：将交互式可视化扩展到超大规模多组学数据并与分析资源集成

• 批准号: 10687189
• 负责人: DAVID H HAUSSLER
• 金额: $ 79.23万
• 依托单位: UNIVERSITY OF CALIFORNIA SANTA CRUZ
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10687189
• 关键词: Acceleration; Architecture; Atlas of Cancer Mortality in the United States; Authorization documentation; Biology; Brain Neoplasms; Cells; Child; Childhood; Collaborations; Communities; Complement; Complex; Computers; Data; Data Analyses; Data Collection; Data Commons; Data Set; Databases; Development; Drug resistance; Education; Educational process of instructing; Engineering; Environment; Galaxy; Genome; Genomics; Genotype-Tissue Expression Project; Growth; Human; Human BioMolecular Atlas Program; Human Genome; Individual; Ingestion; International; Internet; Joints; Link; Malignant Childhood Neoplasm; Maps; Medicine; Methodology; Modeling; Multiomic Data; Organoids; Pediatric Neoplasm; Performance; Population; Pre-Clinical Model; Privatization; Publications; Research; Research Personnel; Resources; Sampling; Secure; Standardization; Tissues; Training; Update; Visualization; Visualization software; Work; analytical tool; anticancer research; cancer genomics; cancer stem cell; cloud based; data access; data harmonization; data integration; data resource; data science infrastructure; data visualization; design; drug development; genome browser; genome resource; genomic signature; improved; indexing; insight; large datasets; multiple omics; next generation; novel therapeutics; outreach; patient derived xenograft model; pre-clinical; prototype; routine practice; scale up; therapeutic evaluation; tool; transcriptome sequencing; tumor; user centered design; virtual

Abstract Two significant paradigm shifts are underway in cancer genomics: single-cell genomic profiling and the growth of the NCI Cancer Research Data Commons. Single-cell genomics is transforming our understanding of complex tumor populations and revealing new insights into tumor composition, microenvironment, cancer stem cells, and drug resistance. Several large-scale, single-cell-focused, national and international projects are currently underway, including HCA, HTAN, and HuBMAP. Data generated by these projects will impact almost every aspect of biology and medicine. For these projects to realize their full potential, it is essential to have data visualization and analysis tools that make these resources accessible to a broad group of biomedical researchers. This is challenging, however, as existing data visualization and analysis tools simply cannot scale to handle these large datasets. The second paradigm shift is NCI’s development of the Cancer Research Data Commons (CRDC), a virtual data science infrastructure that connects cancer research data collections with analytical tools, leveraging the dynamic computing power of the cloud. Efficient and secure incorporation of widely-used 3rd party tools and platforms, including interactive visualization tools such as UCSC Xena, into CRDC is needed to make this resource truly useful. As both of these transitions continue to accelerate in the coming years, they present challenges and opportunities. We propose to enhance UCSC Xena to support and enable these transitions through four aims. Aim 1. We will scale up UCSC Xena by 100x to support the visualization of datasets with greater than 1 million cells (more generally, 1 million bio-entities) without any loss of data or interactivity in the web browser. We will employ several new advances in computer engineering to achieve this performance gain. In addition, we will develop three new visualizations to enable researchers to better explore single-cell data. Aim 2. We will securely integrate UCSC Xena with resources in the NCI CRDC and its community of data analysis tools and platforms. Our integration will make loading ending analysis results into a private Xena Hub in CRDC for visualization in the context of large public data a routine practice. Aim 3. We will provide visualization of the most current cancer genomics resource data through the expansion and update of UCSC Xena database with key projects and datasets. We will collaborate with the Treehouse Childhood Cancer Initiative to build a harmonized preclinical pediatric genomics data resource and make it publicly available on the Xena Browser. This work will leverage PDX models and brain tumor organoids currently being developed and profiled by Dr. Haussler’s group. Aim 4. We will improve user workflows and engagement through User Centered Design, as well as continue user education, support, and outreach.

摘要 癌症基因组学正在进行两个重要的范式转变：单细胞基因组分析和生长 NCI癌症研究数据共享区。单细胞基因组学正在改变我们对 复杂的肿瘤群体并揭示对肿瘤组成、微环境、癌症干细胞的新见解 细胞和耐药性。几个大规模的，单细胞为重点的，国家和国际项目是 目前正在进行中，包括HCA，HTAN和HuBMAP。这些项目产生的数据将影响几乎 生物学和医学的各个方面。为了使这些项目充分发挥其潜力， 必须有 数据可视化和分析工具，使这些资源可访问 一个广泛的生物医学组织， 研究人员然而，这是具有挑战性的，因为现有的数据可视化和分析工具根本无法扩展 来处理这些大型数据集。第二个范式转变是NCI开发的癌症研究数据 Commons（CRDC）是一个虚拟数据科学基础设施，将癌症研究数据收集与 分析工具，利用云的动态计算能力。高效、安全地纳入 广泛使用的第三方工具和平台，包括交互式可视化工具，如UCSC Xena， 需要CRDC使这一资源真正有用。随着这两种转变在世界范围内继续加速， 未来几年，它们将带来挑战和机遇。我们建议加强UCSC Xena，以支持和 通过四个目标实现这些转变。目标1.我们将把UCSC Xena扩展100倍，以支持 具有超过100万个细胞（更一般地，100万个生物实体）的数据集的可视化没有任何损失 数据或网络浏览器中的交互性。我们将利用计算机工程的一些新进展， 实现这一性能提升。此外，我们将开发三种新的可视化，使研究人员能够 更好地探索单细胞数据。目标2.我们将安全地将UCSC Xena与NCI CRDC中的资源集成 及其数据分析工具和平台社区。我们的集成将使加载结束分析 将结果转换为CRDC中的私有Xena Hub，以便在大型公共数据的背景下进行可视化，这是一种常规做法。 目标3。我们将通过扩展提供最新癌症基因组学资源数据的可视化 更新UCSC Xena数据库中的关键项目和数据集。我们将与树屋合作 儿童癌症倡议建立一个协调的临床前儿科基因组学数据资源， 在Xena浏览器上公开提供。这项工作将利用PDX模型和脑肿瘤类器官 豪斯勒博士的团队正在开发和分析目标4。我们将改进用户工作流程， 通过以用户为中心的设计参与，以及继续用户教育，支持和推广。

项目成果

Evaluation of software impact designed for biomedical research: Are we measuring what’s meaningful?

• DOI: 10.48550/arxiv.2306.03255
• 发表时间: 2023-06
• 期刊: ArXiv
• 作者: Awan Afiaz;Andrey Ivanov;J. Chamberlin;D. Hanauer;Candace Savonen;M. Goldman;M. Morgan;Michael Reich;Alexander Getka;Aaron N. Holmes;Sarthak Pati;D. Knight;P. Boutros;S. Bakas;J. Caporaso;G. Fiol;H. Hochheiser;Brian Haas;P. Schloss;James A. Eddy;Jake Albrecht;A. Fedorov;L. Waldron;Ava M. Hoffman;R. Bradshaw;J. Leek;Carrie Wright Department of Biostatistics;U. Washington;Seattle;Wa;Biostatistics Program;Public Health Sciences Division;Fred Hutchinson Cancer Research Center;Departmentof Pharmacology;Chemical Biology;Emory University School of Medicine;Emory University;Atlanta;Ga;Department of Biomedical Informatics;U. Utah;Salt lake City;Ut;Department of MathematicalStatistical Sciences;University of Michigan Medical School;A. Arbor;Mi;University of California at Santa Cruz;Santa Cruz;Ca;Roswell Park Comprehensive Cancer Center;Buffalo;Ny;U. California;San Diego;La Jolla;U. Pennsylvania;Philadelphia;Pa;Jonsson Comprehensive Cancer Center;Los Angeles;I. Health;Department of Genetics;Department of Urology;Pathogen;M. Institute;Northern Arizona University;Flagstaff;Az;U. Pittsburgh;Pittsburgh;Methods Development Laboratory;Broad Institute;Cambridge;Ma;D. Microbiology;Immunology;U. Michigan;Sage Bionetworks;D. Radiology;Brigham;Women's Hospital;H. School;Boston;D. Epidemiology;Biostatistics;City Health;Health Policy;New York.

Reviewers: intercept weaponization of genetics.

评论家：拦截遗传学武器化。

• DOI: 10.1038/d41586-023-00218-7
• 发表时间: 2023
• 期刊: Nature
• 影响因子: 64.8
• 作者: Goldman,MaryJ