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During the training, participants have the opportunity to work on their own data during practical work.\n \nThis training is aimed at doctoral students, engineers, researchers, experienced biological or medical laboratory technicians. It concerns both people who already have an annotation project on the MicroScope platform and wishing to deepen its use, as well as those wishing to learn microbial genomics.\n \n \nIn addition, if you are a user of the MicroScope platform and you have already followed the training \"Annotation and analysis of prokaryotic genomes using the MicroScope platform\" a few years ago we have implemented a new training , the \"MicroScope Platform - Advanced Course\" training in order to update your knowledge on the latest evolutions of the platform and to deepen some of its major functionalities.\n \nThis training, lasting 2 days, will consolidate your use of the platform but also go further:\nPresentation of the evolutions of the MicroScope platform\nPresentation of the new flagship features of the MicroScope platform\nPresentation of tools for RNA-seq analyzes\nDeepening of the functionalities allowing the exploration of the bacterial 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This workshop is tailored for data scientists, advanced Galaxy users, and team leaders who need to scale, automate, and publish their data analysis workflows for batch processing and production-level applications.\r\n\r\nOver five days, you’ll embark on a comprehensive journey through Galaxy’s advanced capabilities:\r\n\r\nMonday: Introduction & Workflow Development\r\n\r\nStart with a welcome and icebreaker to foster collaboration, followed by a brief overview of Galaxy and its workflow features. Dive into hands-on workflow development, where you’ll learn to design clean, efficient workflows, customize them with parameters, and generate user-friendly workflow reports—combining theory with practical application.\r\n\r\nTuesday: Workflow FAIRification, Documentation, and Export\r\n\r\nBegin with a recap of Day 1, then explore UseGalaxy.fr and its unique features. 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The day concludes with an introduction to the “Bring Your Own Work” session.\r\n\r\nThursday: Bring Your Own Work (BYOW)\r\n\r\nDedicate the day to applying your new skills to your own projects. With guidance from trainers, refine your workflows, troubleshoot challenges, and implement solutions using your personal data. Collaborate with peers, document your progress, and optimize your workflows to leave with actionable results for your research.\r\n\r\nFriday: Storage, Data Management, Recap, and Closing\r\n\r\nThe final half-day begins with a recap of the week’s progress, followed by a session on “Bring Your Own Storage”, exploring how to integrate personal or institutional storage with Galaxy. Learn about managing databases in Galaxy and the IDC (Intergalactic Data Commission) effort for efficient data organization. The workshop concludes with a general recap, supplementary exercises, and feedback and closing remarks, ensuring you leave with a comprehensive understanding and resources for continued success.\r\n\r\nThis training will be conducted in French, while the materials (slides) will be in English.\r\n\r\nLearning Objectives\r\nAt the end of the workshop, you will be able to:\r\n\r\nWorkflow development\r\n    Understand the key aspects of workflows by identifying their core components and purpose.\r\n    Create clean, non-repetitive workflows by applying best practices for process design.\r\n    Use workflow parameters to customize and optimize workflows for specific tasks.\r\n    Generate user-friendly workflow reports to display workflow results in a structured way.\r\nWorkflow FAIRyfication\r\n    Annotate a Galaxy workflow with essential metadata to ensure it is findable and reusable.\r\n    Apply best practices to data analysis workflows to improve consistency and interoperability.\r\n    Implement robust tests to validate workflow reliability and accuracy.\r\n    Publish a Galaxy workflow on WorkflowHub and Dockstore via its integration into the IWC, demonstrating enhanced findability,accessibility, interroperability and usability for the scientific community.\r\nWorkflow Documentation\r\n    Design a high-resolution workflow image optimized for documentation and presentations.\r\n    Develop a hands-on tutorial with a “Choose Your Own Tutorial” approach, including:\r\n        A step-by-step tutorial with skeleton generation from the workflow.\r\n        A real-time tutorial that runs and explains the workflow interactively.\r\n    Produce a final documentation package that includes both tutorial formats and high-resolution visuals.\r\nWorkflow Export\r\n    Apply the process of creating a Galaxy Workflow Run RO-Crate by packaging a workflow with its metadata, inputs, and outputs, ensuring it is reproducible and FAIR-compliant.\r\n    Evaluate the completeness and accuracy of a Galaxy Workflow Run RO-Crate by reviewing its structure, metadata, and included files for adherence to best practices.\r\n    Submit a workflow to LifeMonitor, analyzing the platform’s feedback to assess workflow performance and improve its reliability for future use.\r\nWorkflow Scaling using command-line\r\nExecute workflows from the command line using the Planemo run subcommand, demonstrating the ability to run and monitor workflows outside the Galaxy interface.\r\nDevelop simple shell scripts to automate the execution of multiple workflows concurrently or sequentially, optimizing efficiency and scalability.\r\nAnalyze the performance and resource usage of workflows run via shell scripts, evaluating the effectiveness of scaling strategies for large-scale data processing.\r\nScaling Galaxy Use with the API and BioBlend\r\nUtilize the BioBlend library to programmatically interact with Galaxy, executing workflows, managing datasets, and automating repetitive tasks.\r\nDesign a Python script using BioBlend to scale Galaxy workflows for batch processing, ensuring efficient resource use and reproducibility.\r\nEvaluate the performance and scalability of workflows executed via BioBlend, comparing results with manual Galaxy interactions to identify improvements.\r\n“Bring Your Own Work”\r\nApply the concepts and tools learned during the training to develop or refine your own workflows using your personal data, with guidance from trainers.\r\nTroubleshoot challenges in your workflow or data analysis, implementing solutions with the support of trainers and peers.\r\nDemonstrate progress in your project by documenting your workflow, results, and any optimizations made during the sessions.\r\n\r\nRequirements\r\nPrior knowledge and experience using Galaxy\r\nPrior knowledge and experience using command line\r\nFluent in French (materials will be in English and discussions will happen in French)\r\nYour own computer\r\nOptional but encouraged: your own workflow and dataset for the Bring Your Own Work (BYOW) session. 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