Cloud-SPAN: Specialised analyses for environmental 'omics with Cloud-based High Performance Computing

环境生物技术（EB）利用工程微生物系统来解决环境保护、生物修复和资源回收的全球挑战。对英国来说，这是一个关键且不断扩大的领域，支撑着世界上一些最重要的行业。这一点在BBSRC的工业生物技术和生物能源网络（NIBBs）的创建中得到了认可。深入了解参与全球资源生物循环的复杂微生物群落的机制，对于应对净零、废物管理和需求增加等全球挑战至关重要。这些微生物组的复杂性可能比人类肠道中的微生物组要大几个数量级，需要不同的实验设计方法和高性能计算（HPC）分析。然而，EB是一个跨学科领域，吸引了来自数学、工程、生物学、社会科学、管理学、物理和化学等广泛学科的研究人员，而高性能计算系统的大数据组学分析往往不是这些研究人员的核心技能。该提案旨在开发和提供高度可访问的资源，以提高这些跨学科研究人员的技能，使他们能够使用云高性能计算生成和分析与EB相关的大数据。尽管存在微生物组学的基础设施和资源（例如JGI的IMG/M， MG-RAST, Galaxy， CLIMB， EBI），但缺乏与EB领域紧密相关的系统培训，并且文档通常侧重于技术熟练程度，而不是与对实验设计的深刻理解结合起来。我们将提供基础培训，开发并提供新的高级模块，涵盖使用云高性能计算资源生成和分析组学数据所需的专业技能。这将包括实验设计和统计模块，以确保研究人员能够生成适当的数据来调查他们的研究问题。模块将部署由b谷歌教育和亚马逊网络服务（AWS）提供的基于云的容器化实例，以向学习者免费提供示例工作流程。它们将形成一个完整的培训资源，具有明确的先决条件和学习目标，可用于面对面或在线导师指导的研讨会或自定进度学习。我们的建议提供了结构化的学习路径，从稳健的实验设计所需的统计技能，到HPC组学分析的可重复执行和解释，以满足具有不同经验水平的研究人员的需要，并允许对培训需求进行自我评估。我们还提供多元化奖学金，使代表性不足的群体成员能够参加在线或面对面的培训。约克大学与软件可持续发展研究所（SSI）的合作将数据科学教学法和环境组学研究的卓越成果与SSI在研究计算和社区建设方面的英国领先专业知识结合在一起。这将确保所编制的培训真正补充和符合现有材料，以加强国家提供。通过使资源可查找、可访问、可互操作和可重用（FAIR），为部署提供跨平台图像，通过开发和积极参与实践社区，并为参与者自己的数据提供支持方法实践的代码务虚会，将促进可持续性。此外，将为机构HPC团队开发“云管理指南”，以使用自己的资源运行专门的模块。这些指南将由Cloud-SPAN系统管理员提供1到2天的培训。该项目将由我们的合作伙伴，SSI，谷歌教育，aws和N8卓越计算密集型研究中心，并通过提供会议演讲和研讨会来推广。

Environmental Biotechnology (EB) addresses global challenges using engineered microbial systems for environmental protection, bio-remediation and resource recovery. It is a critical and expanding area for the UK and underpins some of the world's most important industries. This is acknowledged by the funding invested in the creation of BBSRC's Networks in Industrial Biotechnology and Bioenergy (NIBBs). A deep mechanistic understanding of the complex microbial communities involved in the biological cycling of global resources is essential to meet global challenges such as Net Zero, waste management and increased demand. The complexity of these microbiomes can be orders of magnitude larger than those found in the human gut, requiring different approaches to experimental design and analysis with High Performance Computing (HPC). However, EB is an interdisciplinary field that attracts researchers from a broad range of disciplines including Mathematics, Engineering, Biology, Social Sciences, Management, Physics and Chemistry and big data 'omics analyses on HPC systems are often not core skills for such researchers.This proposal aims to develop and deliver highly accessible resources that will upskill these interdisciplinary researchers so that they are able to generate and analyze big data relating to EB using Cloud HPC. Although infrastructure and resources exist for microbial 'omics (e.g. JGI's IMG/M, MG-RAST, Galaxy, CLIMB, EBI) there is a lack of systematic training tightly linked to the EB domain and documentation is often focussed on technical proficiency rather than contextualised with a strong understanding of experimental design. We will provide foundational training and develop and deliver new advanced modules covering the specialised skills required to generate and analyse 'omics data using Cloud HPC resources. These will include experimental design and statistical modules to ensure researchers can generate data appropriate to investigate their research question. Modules will deploy cloud-based containerised instances provided by Google Education and Amazon Web Services (AWS) for exemplar workflows free to the learner. They will form a complete training resource with fully articulated prerequisites and learning objectives that can be used for in-person or online tutor-led workshops or self-paced learning. Our proposal offers structured Learning Paths from the statistical skills required for robust experimental design through to the reproducible execution and interpretation of 'omics analyses with HPC to cater to researchers with differing levels of previous experience and which allow self-assessment of training needs. We also provide Diversity Scholarships to enable members of underrepresented groups to participate in online or in-person training.The collaboration between the University of York and the Software Sustainability Institute (SSI) brings together excellence in data science pedagogy and environmental 'omics research with the SSI's UK-leading expertise in research computing and community building. This will ensure the training developed genuinely complements, and aligns with, existing materials to enhance national provision. Sustainability will be fostered by making the resources Findable, Accessible, Interoperable and Reusable (FAIR), providing cross-platform images for deployment and by developing and proactively engaging with a Community of Practice and providing Code Retreats for the supported practice of methods to participants' own data. In addition, "Cloud Administration Guides" will be developed for institutional HPC Teams to run specialised modules with their own resources. These Guides will be supported 1-to-2 day training by Cloud-SPAN systems administrators. The project will be promoted by our partners, the SSI, Google Education, AWSand the N8 Centre of Excellence in Computationally Intensive Research and through delivery of conference talks and seminars.