DataJoint Pipelines for Neurophysiology

神经生理学 DataJoint 管道

• 批准号: 10437673
• 负责人: Dimitri Yatsenko
• 金额: $ 75.65万
• 依托单位: VATHES INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10437673
• 关键词: Adopted; Adoption; Algorithms; Architecture; Atlases; BRAIN initiative; Behavior; Books; Brain; Calcium; Cells; Classification; Cloud Service; Collection; Custom; Data; Data Analyses; Data Collection; E-learning; Electron Microscopy; Electrophysiology (science); Face; Fostering; Guidelines; Image; International; Learning; Libraries; Methods; Modality; Neurosciences; Nomenclature; Ontology; Output; Persons; Positioning Attribute; Problem Sets; Research; Resource Informatics; Sampling; Scientist; Sensory; Sorting - Cell Movement; Techniques; Transgenic Organisms; Virus; Work; base; complex data; computerized data processing; data ecosystem; data integrity; data pipeline; data sharing; data tools; design; diverse data; experimental study; hackathon; imaging Segmentation; informatics tool; light microscopy; neurophysiology; online resource; open source; tool; transcriptomics

The field of neuroscience and the BRAIN Initiative in particular are amassing a wealth of informatics resources for managing, analyzing, and sharing data. Yet every lab must solve similar sets of problems to integrate these tools into the particular workflows of their experiments: data entry, acquisition, processing, analysis, and vi­sualization. We created DataJoint: an open-source general framework for experiment data pipelines and col­laborative automated workflows . Either independently or with support from our company, dozens of research groups have adopted DataJoint for diverse data modalities such as multielectrode electrophysiology, calcium imaging, light and electron microscopy, behavior tracking, sensory stimulation, transcriptomics, and optoge­netics. In these complex data ecosystems, DataJoint enables groups of scientists to collaborate with clear work­ flows while sharing data continuously and conserving data integrity. To disseminate and integrate shared data pipelines into neuroscience practice, we propose to compile and dis­seminate a library of DataJoint Pipelines for Neurophysiology. We will extract essential motifs from DataJoint­ based open projects and organize them by data modality into a collection of curated, mutually-compatible modules stringing together data collection and computation. Documented and ready for de novo deployment, the modules will feature ancillary tools for data entry (electronic lab books), interactive graphical user inter­ faces adapted from existing projects (e.g. customizable data processing steps integrating popular algorithms for image segmentation and spike sorting), and integration of existing brain atlases, coordinate frameworks, ontologies for cell classification , and nomenclatures for viruses and transgenic lines. To foster uniform ontolo­gies, we will harmonize these pipelines with emerging neurodata standards. The results of this work will be administered as an online resource showcasing the pipelines along with sample data, executable demos, and guidelines for deployment. Visitors will be able to customize, extend, and combine the modules into complete pipelines suitable for their particular experiments and learn the techniques for building new solutions. The modules will support diverse computing architectures, including specialized hardware and cloud services. We will also conduct web-based trainings and in-person hackathons to help accelerate the adoption of these tools in working neuroscience labs. Vathes LLC is uniquely positioned to perform this work as we co-develop data pipelines for collaborative projects such as IARPA's MICrONS, International Brain Lab, and BRAIN Initiative Ul9 pro jects. The output of this project will enable many new research groups to adopt DataJoint and to effectively integrate informatics tools into neuroscience practice.

神经科学领域，尤其是大脑计划，正在积累丰富的信息学资源，用于管理、分析和共享数据。然而，每个实验室都必须解决类似的问题，才能将这些工具整合到他们实验的特定工作流程中：数据输入、获取、处理、分析和可视化。我们创建了DataJoint：一个用于实验数据管道和协作自动化工作流的开源通用框架。无论是独立还是在我们公司的支持下，数十个研究小组已经将DataJoint应用于各种数据模式，如多电极电生理学、钙成像、光学和电子显微镜、行为跟踪、感觉刺激、转录和光扫描。在这些复杂的数据生态系统中，DataJoint使科学家团队能够通过清晰的工作流进行协作，同时持续共享数据并保护数据完整性。 为了将共享数据管道传播和集成到神经科学实践中，我们建议汇编和描述一个神经生理学数据连接管道图书馆。我们将从基于DataJoint的开放项目中提取必要的主题，并按照数据模式将它们组织成一个集合，这些模块经过精心策划，相互兼容，将数据收集和计算串联在一起。这些模块已记录在案，可随时重新部署，将具有数据输入的辅助工具(电子实验室书籍)、根据现有项目改编的交互式图形用户界面(例如，结合图像分割和棘波分类的流行算法的可定制数据处理步骤)，以及整合现有的脑图谱、坐标框架、用于细胞分类的本体论以及病毒和转基因系的命名。为了促进统一的本体，我们将使这些管道与新兴的神经数据标准相协调。这项工作的结果将作为一个在线资源进行管理，展示管道以及示例数据、可执行演示和部署指南。参观者将能够定制、扩展和组合这些模块，形成适合他们特定实验的完整管道，并学习构建新解决方案的技术。这些模块将支持不同的计算架构，包括专门的硬件和云服务。我们还将进行基于网络的培训和面对面的黑客松，以帮助加快这些工具在神经科学实验室中的应用。Vathes LLC在为IARPA的微米、国际脑实验室和脑倡议Ul9项目等合作项目共同开发数据管道时，处于执行这项工作的独特地位。该项目的成果将使许多新的研究小组采用DataJoint，并将信息学工具有效地整合到神经科学实践中。