A visualization interface for BRAIN single cell data, integrating transcriptomics, epigenomics and spatial assays

BRAIN 单细胞数据的可视化界面，集成转录组学、表观基因组学和空间分析

• 批准号: 10643313
• 负责人: Maximilian Haeussler
• 金额: $ 86.63万
• 依托单位: UNIVERSITY OF CALIFORNIA SANTA CRUZ
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10643313
• 关键词: Acceleration; Address; Adopted; Algorithmic Analysis; Algorithms; Archives; Atlases; BRAIN initiative; Biological Assay; Biological Sciences; Brain; Cells; Cellular Assay; Censuses; Chromosomes; Collection; Computer Analysis; Computer software; Custom; Data; Data Analyses; Data Display; Data Files; Data Set; Databases; Dimensions; Environment; Funding; Future; Gene Expression; Genes; Genomics; Hour; Human; Image; Internet; Knowledge; Location; Maps; Metadata; Methylation; Microscopy; Modality; Molecular; Online Systems; Ontology; Pattern; Physiology; Process; Provider; Publications; Reaction Time; Research Personnel; Retrieval; Risk; Running; Security; Side; Slice; Specific qualifier value; Standardization; Structure; Technology; Testing; Time; United States National Institutes of Health; Universities; Visualization; Visualization software; Work; Writing; XCL1 gene; brain cell; cell type; cloud storage; computerized tools; data access; data archive; data centers; data management; data portal; data reuse; data sharing; data structure; data visualization; design; differential expression; distributed archives; epigenomics; field study; file format; flexibility; genome browser; improved; interest; open data; sex; success; tool; transcriptomics; user-friendly; web site

PROJECT SUMMARY / ABSTRACT The BRAIN Initiative’s -omics data archive NeMO contains all the BICCN single cell single cell data, more than one million files at the time of writing. However, no interactive visualization interface to inspect these results is available and many researchers are not proficient enough with computational tools (download data, convert, load, plot) to take advantage of the data in NeMO. This makes testing hypotheses by non-computational researchers a lot harder than necessary but the input from these domain experts and their knowledge about molecular processes and cell specification is crucial for the interpretation of the data. Here, I propose to repeat for the single cell field what has made genome browsers a pillar of data sharing: a standard file format and a visualization tool for it. A new format is a requirement, because in the era of cloud technology and distributed archives, data is usually not stored locally anymore. Sub-second reaction times from remote storage are necessary for visualization and possible but existing single cell file formats were not designed for this access pattern. In addition, for NeMO, being able to keep all results of a single cell assay in one defined structure makes data management and access easier. We will define such a format, it will integrate all the main analysis results and will convert all existing processed data in NeMO (not the raw read data) to the new format. We will then make the data available for interactive exploration directly on the NeMO website via our UCSC Cell Browser, which is already running on different University websites. It is actively used already by thousands of researchers every month to visualize hundreds of single datasets that we collected at UCSC and has been used for hundreds of scientific publications. We will extend our tool to provide direct support for the most recent assay and analysis types, mainly ATAC, methylation and spatial transcriptomics imaging data and integrate the UCSC Genome Browser for chromosome-level views and summaries. An improved split-screen mode will allow visualizing both spatial and transcriptomic data at the same time. In addition, the Cell Browser will allow users to run the most fundamental and well-known analysis algorithms on any subset of cells, with a focus on fast response time so that researchers do not have to download the whole dataset to get differential genes, dimensionality reduction or specific sub-clustering results of a few selected cell clusters of interest. Integrating these software features and the NeMO data into a single user-friendly environment will make sure that the BICCN -omics data can be accessed as easily as possible, which will help accelerate the path to discovery from the wealth of BRAIN single cell datasets being produced right now and in the future.

项目摘要 /摘要 大脑倡议的 - 组数据存档NEMO包含所有BICCN单细胞单细胞数据，更多 写作时超过一百万个文件。但是，没有交互式可视化接口可以检查这些 结果可用，许多研究人员不够精通计算工具（下载数据， 转换，负载，图）以利用Nemo中的数据。这使得通过 非竞争研究人员比必要的要困难得多，但是这些领域专家及其的投入 关于分子过程和细胞规范的知识对于数据解释至关重要。 在这里，我建议重复单个单元格的原因是什么使基因组浏览了数据共享的支柱：a 标准文件格式和可视化工具。新格式是一种要求，因为在云时代 技术和分布式档案，数据通常不再在本地存储。亚秒反应时间 从远程存储中需要可视化和可能的可能，但现有的单手单元文件格式不是 为此访问模式设计。另外，对于Nemo，能够将单个单元格测定的所有结果保留在 一个定义的结构使数据管理和访问更加容易。我们将定义这样的格式，它将 集成了所有主要分析结果，并将转换Nemo中的所有现有处理数据（不是原始读取 数据）到新格式。 然后，我们将通过我们的UCSC直接在NEMO网站上进行交互式探索数据 细胞浏览器，该浏览器已经在不同的大学网站上运行。它已经被数千人积极使用 每个月的研究人员都可以想象我们在UCSC收集的数百个数据集 用于数百个科学出版物。我们将扩展我们的工具，以直接支持最近 测定和分析类型，主要是ATAC，甲基化和空间转录组学成像数据，并整合 UCSC基因组浏览器用于染色体级别的观点和摘要。改进的分屏模式将 允许同时可视化空间和转录组数据。此外，单元浏览器将允许 用户在任何子集上运行最基本和众所周知的分析算法，重点是 快速响应时间，因此研究人员不必下载整个数据集即可获得差异基因， 几个选定的感兴趣的细胞簇的尺寸降低或特定的子聚类结果。 将这些软件功能和NEMO数据集成到单个用户友好的环境中 确保可以尽可能轻松地访问BICCN - 组数据，这将有助于加速通往 从现在和将来生产的大量脑单细胞数据集中发现。