Handles creating, reading and updating training events.

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            "name": "Analysis of shotgun metagenomic data",
            "shortName": "",
            "description": "This training session is organized by the Genotoul bioinfo platform. This course is dedicated to the analysis of prokaryotic shotgun metagenomic data from Illumina and Pacbio HiFi sequencing technology. \r\n\r\nAfter an overview of metagenomics and the biases and limitations of analyses, we will look at the main steps involved in analysing metagenomic data and launch independent tools on the genobioinfo cluster.\r\nLearners will then test a workflow to automate processing on a test dataset (metagWGS ).\r\nOn the third day, learners will choose which analysis strategy to start with according to their experimental design and launch the first stage of metagWGS on their own data.\r\nBy the end of the course, trainees will be familiar with the scope, advantages and limitations of shotgun sequencing data analysis and will have started the analysis on their own data.\r\n\r\ncalendar\r\n \r\n\r\nThis training is focused on practice. It consists of several modules with a large variety of exercises:\r\n\r\nFirst Day\r\nStart at 09:00 am\r\nTour de table\r\nIntroduction to metagenomics, Illumina and Pacbio data, analysis stages, analysis limits, etc.\r\nPresentation of some key tools for each stage\r\nPractical work on the main stages launched independently\r\nEnd at 17:00 pm\r\nSecond Day\r\nStart at 09:00 am\r\nIntroduction to the advantages and disadvantages of workflows and containers\r\nLaunch of the data cleansing stage\r\nLaunch of the rest of the workflow and analysis of the multiQC report\r\nEnd at 17:00 pm\r\nThird Day – BYOD\r\nStart at 09:00 am\r\nDefine the analysis strategy and launch the start of the analysis of your own data.\r\nEnd at 17:00 pm maximum",
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                "Non-academic for non-academic: 1650€ + 20% taxes (TVA)",
                "Academic non-INRAE for academic but non-INRAE: 510 € + 20% taxes (TVA)",
                "INRAE for INRAE's staff: 450 € no VAT charged"
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            "topics": [
                "http://edamontology.org/topic_3174"
            ],
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                "NGS Data Analysis",
                "Metagenomics"
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                "Linux/Unix",
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                    "id": 82,
                    "name": "INRAE",
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                },
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                    "id": 37,
                    "name": "MIAT - Mathématiques et Informatique Appliquées de Toulouse",
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            "logo_url": "https://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png",
            "updated_at": "2025-12-09T09:19:28.199012Z",
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            "id": 298,
            "name": "LINUX",
            "shortName": "",
            "description": "This training session is organized by the Genotoul bioinfo platform and aims at learning sequence analysis. This training session has been designed to familiarize yourself with the platform resources and its organization. You will learn to access the platform from your work station, what is an Linux environment and how to use it, how to create and manipulate files, how to transfer them from and to your personal computer.\r\n\r\nThis training is focused on practice. It consists of 3 modules with a large variety of exercises:\r\n\r\n- Connect to « genotoul » server (09:00 am to 10:30 am): Platform presentation, Linux basics, opening an user account, Putty installation, first connection.\r\n- Files and basics commands  (10:45 am to 12:00 pm): types of files and secure access, file manipulation commands, text editors and viewers, disk space management .\r\n- Transfers and file manipulation (14:00 pm to 17:00 pm): download/transfer, compress/uncompress, utility commands and data extraction, output redirections.",
            "homepage": "https://bioinfo.genotoul.fr/index.php/events/linux-2-2/",
            "is_draft": false,
            "costs": [
                "Non-academic: 550€ + 20% taxes (TVA)",
                "Academic but non-INRAE: 170 € + 20% taxes (TVA)",
                "For INRAE's staff: 150 € no VAT charged;"
            ],
            "topics": [
                "http://edamontology.org/topic_3316"
            ],
            "keywords": [],
            "prerequisites": [
                "none"
            ],
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            "logo_url": "https://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png",
            "updated_at": "2025-12-09T09:42:16.231660Z",
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            "trainingMaterials": [
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                    "name": "Linux slides - Genotoul-bioinfo",
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                    "id": 138,
                    "name": "Linux TP - Genotoul-bioinfo",
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            "learningOutcomes": "You will learn to access the platform genotoul bioinfo from your work station, what is an Linux environment and how to use it, how to create and manipulate files, how to transfer them from and to your personal computer.",
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            "id": 303,
            "name": "Tools for phylogenetic analysis",
            "shortName": "",
            "description": "You will learn How to find homologs, make multiple alignments, reconstruct the phylogeny, visualize the tree.\r\n\r\nAt the end of the workshop, you will be able to use web tools to reconstruct accurate phylogenies.\r\n\r\nUnless all participants speak French, the course will be taught in English.",
            "homepage": "https://pliniuscursus.univ-amu.fr/formation/tools-for-phylogenetic-analysis/",
            "is_draft": false,
            "costs": [
                "Free to academics"
            ],
            "topics": [
                "http://edamontology.org/topic_0084"
            ],
            "keywords": [],
            "prerequisites": [
                "Master"
            ],
            "openTo": "Internal personnel",
            "accessConditions": "The first sessions are only available for IM2B students.",
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                    "id": 38,
                    "name": "IGS - Laboratoire Information Génomique et Structurale",
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            ],
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                    "id": 23,
                    "name": "PACA-Bioinfo",
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            ],
            "logo_url": null,
            "updated_at": "2022-06-02T11:50:50.812642Z",
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            ],
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            ],
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            "trainingMaterials": [],
            "learningOutcomes": "",
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        },
        {
            "id": 289,
            "name": "Introduction to galaxy: looking for variants in prokaryotes",
            "shortName": "Introduction to galaxy",
            "description": "This course will focus on the technical aspects of using a galaxy server. Accessible without any prerequisite in computer science, it will allow you to master the different fundamental tools of galaxy and will open the doors of bioinformatics analysis for your different projects.\r\nDifferent questions will be addressed through an example of variants analysis in a prokaryotic organism. At the end of this course, on any accessible galaxy instance, you will be able to:\r\n- upload your data\r\n- map them on a reference genome\r\n- find the variants (SNPs) and analyze the results\r\n- generate, manipulate and share your workflows, data and histories\r\n- find the right tools for other analyses and use them in your own project.\r\n\r\nUnless all participants speak French, the course will be taught in English.",
            "homepage": "https://pliniuscursus.univ-amu.fr/formation/galaxy-platform/",
            "is_draft": false,
            "costs": [
                "Free to academics"
            ],
            "topics": [
                "http://edamontology.org/topic_0091",
                "http://edamontology.org/topic_0622"
            ],
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            "prerequisites": [
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            "logo_url": null,
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        {
            "id": 313,
            "name": "RNA-Seq analysis",
            "shortName": "",
            "description": "Introduction to RNA-Seq analysis",
            "homepage": "https://southgreenplatform.github.io/trainings//rnaseq/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [],
            "keywords": [],
            "prerequisites": [
                "Linux - Basic Knowledge"
            ],
            "openTo": "Internal personnel",
            "accessConditions": "Open to South Green close collaborators",
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            ],
            "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png",
            "updated_at": "2023-12-04T15:04:39.023455Z",
            "audienceTypes": [],
            "audienceRoles": [],
            "difficultyLevel": "Intermediate",
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            "hoursHandsOn": 8,
            "hoursTotal": 14,
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                "https://catalogue.france-bioinformatique.fr/api/event/471/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/event/563/?format=api"
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        },
        {
            "id": 312,
            "name": "Introduction to python",
            "shortName": "",
            "description": "This course provides an introduction to programming using python. At the end of the training, participants should be able to write simple python programs to handle biological data and to understand more complex programs written by others.\r\nNote : This course in currently available only in french",
            "homepage": "https://southgreenplatform.github.io/trainings//python/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [],
            "keywords": [],
            "prerequisites": [
                "Linux - Basic Knowledge"
            ],
            "openTo": "Internal personnel",
            "accessConditions": "Open to South Green close collaborators",
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                    "name": "South Green",
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            ],
            "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png",
            "updated_at": "2022-06-02T11:50:50.812642Z",
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            "hoursPresentations": 10,
            "hoursHandsOn": 18,
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            "event_set": [
                "https://catalogue.france-bioinformatique.fr/api/event/470/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/event/556/?format=api"
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        },
        {
            "id": 365,
            "name": "BIGomics, Génomique Comparative",
            "shortName": "BOGC",
            "description": "Ce module vise à fournir une expérience d’analyse de données de génomique.\r\nLes technologies Next Generation Sequencing (NGS) ont conduit à une production massive de\r\ndonnées « Omiques » pour les plantes cultivées majeures, ce qui demande de nouvelles\r\napproches d’analyses haut débit. La connaissance de ces approches et des outils qui en\r\ndécoulent pour analyser la séquence et la structure des génomes, les annoter et caractériser\r\nleur diversité et leurs profils d’expression permet d’aborder des questions de recherche\r\nbiologique avancée sur la diversité et l’adaptation des plantes. Les espèces prises en\r\nconsidération sont des espèces phares des instituts de recherche agronomique de Montpellier\r\net font partie des cultures les plus importantes pour l’agriculture mondiale. Des plateformes\r\nd’outils bioinformatiques récents reposant sur des centres de calcul et de stockage haute\r\ncapacité, sont en place pour analyser des jeux de données originales permettant de mieux\r\ncomprendre comment les génomes de plantes évoluent et s’expriment. L’ensemble de ces\r\nconnaissances Findable, Accessible, Interoperable, Reusable car intégré dans des systèmes\r\nd’information peut soutenir l'identification de gènes responsables de caractères adaptatifs ou\r\nde production. La mobilisation de jeunes chercheurs sur ces sujets est primordiale tant la\r\ndemande est importante.\r\nLe module est structuré sous la forme de cours et de travaux tutorés avec la rencontre de\r\ngénéticiens et de bioinformaticiens permettant d’appréhender les formes variées des progrès\r\nen bioanalyse génomique. Il permet d’acquérir les lignes directrices pour l’accès, l'utilisation\r\net l'analyse de différents types de données omique (e.g. (épi)génomique, transcriptomique,\r\nprotéique, métabolique) en vue d’accélérer les recherches en génomique fonctionnelle et\r\nbiotechnologie des plantes.\r\nL’évaluation sera faite sur la base de la participation et de la qualité du projet proposé par\r\nl’étudiant en fin de module, individuellement ou en binôme, suivant les consignes détaillées en\r\ndébut de module",
            "homepage": "https://bioagro.edu.umontpellier.fr/files/2021/04/HAA906V_Bigomics.pdf",
            "is_draft": false,
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                "Free to academics"
            ],
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                "http://edamontology.org/topic_0797",
                "http://edamontology.org/topic_3810",
                "http://edamontology.org/topic_3056",
                "http://edamontology.org/topic_0780"
            ],
            "keywords": [
                "Phylogeny",
                "Biodiversity",
                "NGS Data Analysis"
            ],
            "prerequisites": [
                "Basic knowledge of R"
            ],
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            "accessConditions": "Inscription via un formulaire Moodle",
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                    "id": 85,
                    "name": "IRD",
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                },
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                    "id": 82,
                    "name": "INRAE",
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                    "id": 24,
                    "name": "South Green",
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            ],
            "logo_url": "https://raw.githubusercontent.com/SouthGreenPlatform/trainings/gh-pages/images/southgreenlong.png",
            "updated_at": "2024-03-20T11:30:31.480815Z",
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        },
        {
            "id": 294,
            "name": "Linux for Dummies",
            "shortName": "",
            "description": "This course offers an introduction to work with Linux. We will describe the Linux environment, the first linux commands so participants can start to utilize command-line tools and feel comfortable using bioinformatics softwares through a linux terminal",
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            "is_draft": false,
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            "keywords": [],
            "prerequisites": [],
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            "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png",
            "updated_at": "2023-12-04T15:05:31.847400Z",
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            "hoursTotal": 7,
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                "https://catalogue.france-bioinformatique.fr/api/event/555/?format=api"
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        },
        {
            "id": 287,
            "name": "Introduction to Oxford Nanopore Technology data analyses",
            "shortName": "Introduction to ONT data analyses",
            "description": "This course offers an introduction to ONT data analysis. It includes 5 issues: basecalling, reads quality control, assemblies and polishing/correction, contig quality and structural variants detection.",
            "homepage": "https://southgreenplatform.github.io/trainings//ont/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
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                "http://edamontology.org/topic_3673",
                "http://edamontology.org/topic_0196",
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                "Biologists"
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            "difficultyLevel": "Novice",
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                }
            ],
            "learningOutcomes": "* Understanding limits and advantages of ONT technology\r\n* Manipulating ONT data on a virtual machine on jupyter environment\r\n* Handling mapping, assembly, polishing tools and be able to analyse your own data\r\n* Detecting structural variations using long reads",
            "hoursPresentations": 6,
            "hoursHandsOn": 6,
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                "https://catalogue.france-bioinformatique.fr/api/event/450/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/event/562/?format=api"
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        },
        {
            "id": 256,
            "name": "RNASeq analyses (using Galaxy and TOGGLe)",
            "shortName": "",
            "description": "This course offers an introduction to RNASeq analyses using two different workflow management systems: Galaxy and TOGGLe. This includes reference-based mapping, estimates of transcript levels, differential expression (DE) analyses, visualization of statistics results.\r\nPrerequisites\r\nWorkflow management system (Galaxy, TOGGLe)\r\n\r\nProgram\r\nMapping of RNASeq against a transcriptome reference with kallisto (Galaxy)\r\nMapping of RNASeq against an annotated genome reference with TopHat (TOGGLe)\r\nDifferential expression analysis using EdgeR and DESeq2\r\nPlots, clustering, co-expression network: degust, WGCNA\r\n\r\n\r\nLearning objectives\r\nManipulate packages/tools available for searching DE genes\r\nThink about different normalisation methods\r\nDetect differentially expressed genes\r\nCompare results between two approaches\r\n\r\n\r\nInstructors\r\nAlexis Dereeper - alexis.dereeper@ird.fr\r\nSebastien Cunnac - sebastien.cunnac@ird.fr\r\nSebastien Ravel - sebastien.ravel@cirad.fr\r\nChristine Tranchant  - christine.tranchant@ird.fr",
            "homepage": "https://southgreenplatform.github.io/trainings//rnaseq/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [],
            "keywords": [],
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            "openTo": "Internal personnel",
            "accessConditions": "Open to South Green close collaborators",
            "maxParticipants": null,
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                    "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api"
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            ],
            "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png",
            "updated_at": "2023-01-24T10:26:00.180547Z",
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        },
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            "id": 349,
            "name": "Reproducible Research",
            "shortName": "",
            "description": "The following topics and tools are covered in the course:\r\n\r\n    Data management\r\n    Project organisation\r\n    Git\r\n    Conda\r\n    Snakemake\r\n    Nextflow\r\n    R Markdown\r\n    Jupyter\r\n    Docker\r\n    Singularity\r\n\r\nAt the end of the course, students should be able to:\r\n\r\n    Use good practices for data analysis and management\r\n    Clearly organise their bioinformatic projects\r\n    Use the version control system Git to track and collaborate on code\r\n    Use the package and environment manager Conda\r\n    Use and develop workflows with Snakemake and Nextflow\r\n    Use R Markdown and Jupyter Notebooks to document and generate automated reports for their analyses\r\n    Use Docker and Singularity to distribute containerized computational environments",
            "homepage": "https://southgreenplatform.github.io/training_reproducible_research/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [],
            "keywords": [],
            "prerequisites": [
                "Linux - Basic Knowledge"
            ],
            "openTo": "Internal personnel",
            "accessConditions": "Open to South Green close collaborators",
            "maxParticipants": 20,
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                    "name": "South Green",
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            ],
            "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png",
            "updated_at": "2023-12-04T15:16:00.921744Z",
            "audienceTypes": [],
            "audienceRoles": [],
            "difficultyLevel": "Novice",
            "trainingMaterials": [],
            "learningOutcomes": "At the end of the course, students should be able to:\r\n\r\n    Use good practices for data analysis and management\r\n    Clearly organise their bioinformatic projects\r\n    Use the version control system Git to track and collaborate on code\r\n    Use the package and environment manager Conda\r\n    Use and develop workflows with Snakemake and Nextflow\r\n    Use R Markdown and Jupyter Notebooks to document and generate automated reports for their analyses\r\n    Use Docker and Singularity to distribute containerized computational environments",
            "hoursPresentations": 8,
            "hoursHandsOn": 13,
            "hoursTotal": 21,
            "personalised": null,
            "event_set": [
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        },
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            "id": 255,
            "name": "Initiation to NGS Workflow Managers developed within the South Green Platform: Galaxy and TOGGLe",
            "shortName": "",
            "description": "This course introduces the 2 commonly used workflow managers in the South Green Bioformatics platform, both in a theoretical and practical way, with hands-on practice sessions. It will help you to quickly develop and run your own pipelines using these tools through an graphical user or command-line interface.\n \nPrerequisites\nPrior knowledge of workflow managers not necessary Basic knowledge of Linux (Linux for dummies required) - TOGGLe practical\n\nProgram\nWhy using a workflow manager to analyse data ?\nHow to perform an analysis ?\nHow to create your own workflow ?\nHow to execute it?\nUse case\n\n\nLearning objectives\nExplaining what Workflow Managers are,\n\tin which way they differ from each other.\nHow you can use them in your research.\nCreating your own workflow\nAnalysing your NGS data with Galaxy and TOGGLe\n\n\nInstructors\nAlexis Dereeper (AD) - alexis.dereeper@ird.fr\nSebastien Ravel (SR) - sebastien.ravel@cirad.fr\nChristine Tranchant (CT) - christine.tranchant@ird.fr\n\n",
            "homepage": "https://southgreenplatform.github.io/trainings//galaxyToggle/",
            "is_draft": false,
            "costs": [
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            ],
            "topics": [],
            "keywords": [],
            "prerequisites": [],
            "openTo": "Internal personnel",
            "accessConditions": "",
            "maxParticipants": null,
            "contacts": [],
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                    "id": 24,
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                    "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api"
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            ],
            "logo_url": "",
            "updated_at": "2022-06-02T11:50:50.812642Z",
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            ]
        },
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            "id": 348,
            "name": "Advanced HPC Trainings",
            "shortName": "",
            "description": "This course continues the explanation on how to work on HPC Southgreen clusters. It is intended for experienced users, with the goals of improving LC user productivity and minimizing the obstacles. New notions and tools are presented such as job arrays, basic softwares installation,module environment and singularity. All these notions will be developped.",
            "homepage": "https://southgreenplatform.github.io/trainings//Advanced_HPC/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [],
            "keywords": [
                "HPC",
                "SLURM"
            ],
            "prerequisites": [],
            "openTo": "Internal personnel",
            "accessConditions": "Oprn to South Green close collaborators",
            "maxParticipants": 20,
            "contacts": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/589/?format=api"
            ],
            "elixirPlatforms": [],
            "communities": [],
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            "organisedByOrganisations": [
                {
                    "id": 85,
                    "name": "IRD",
                    "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IRD/?format=api"
                }
            ],
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                {
                    "id": 24,
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                }
            ],
            "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png",
            "updated_at": "2023-12-04T14:46:58.108350Z",
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                "Professional (continued)"
            ],
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                "All"
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            "event_set": [
                "https://catalogue.france-bioinformatique.fr/api/event/557/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/event/565/?format=api"
            ]
        },
        {
            "id": 254,
            "name": "Analyse de données NGS dédiée à la génomique végétale en Afrique de l'Ouest",
            "shortName": "",
            "description": "Les avancées spectaculaires des technologies de séquençage de 2ème et 3ème génération sont une véritable révolution pour la recherche en science de la vie. Ces techniques permettent le séquençage en quelques semaines de génomes entiers d’organismes complexes, générant une explosion du volume de données génomiques. \n\t\t\tToutefois l’analyse de telles masses d’informations nécessite des compétences en linux, en bioinformatique ainsi qu’une bonne connaissance et maîtrise de nombreux algorithmes et logiciels. La réalisation de ces analyses nécessite également l’accès à des ressources de calcul telles que des clusters de calcul. \n\t\t\tLe DP IAVAO et le LMI LAPSE en collaboration avec la plateforme bioinformatique South Green organisent, du 4 au 12 Octobre 2018, une formation en bioinformatique dédié à l’analyse de données de séquençage dont les objectifs sont de présenter les technologies de séquençage et les différentes analyses bioinformatiques pour exploiter au mieux cette masse de données afin de pouvoir réaliser des projets génomiques à grande échelle sur leurs modèles (plantes et pathogènes).\nPrérequis\nAucun\n\nProgramme\nLinux et lignes de commandes \nInitiation à l’utilisation du cluster du CERAAS \nPrésentation des technologies de séquençages \nAppel de SNP sur des données WGS \nPost analyse de données de SNPs\nOutils Genome Harvest \n\n\nObjectifs\nAprès la formation, les participants seront capables de :\nse connecter à un cluster Linux\nlancer des programmes/analyses bioinformatiques\ndéfinir les étapes pour analyser des données de séquençage\nanalyser des données de séquençage\nutiliser des gestionnaires de workflow tel que Galaxy ou TOGGLe\n\n\nInstructors\nChristine Tranchant (CT) - christine.tranchant@ird.fr\nNdomassi Tando (NT) - ndomassi.tando@ird.fr\nBertrand Pitollat (BP) - bertrand.pitollat@cirad.fr\nFrançois Sabot (SB) - francois.sabot@ird.fr\nManuel Ruiz (MR) - manuel.ruiz@cirad.fr\nGautier Sarah (GS) - gautier.sarah@cirad.fr\n\n",
            "homepage": "https://southgreenplatform.github.io/trainings//ngsTrainings/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
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            "keywords": [],
            "prerequisites": [],
            "openTo": "Internal personnel",
            "accessConditions": "",
            "maxParticipants": null,
            "contacts": [],
            "elixirPlatforms": [],
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            "organisedByOrganisations": [
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                    "name": "LAPSE",
                    "url": "https://catalogue.france-bioinformatique.fr/api/organisation/LAPSE/?format=api"
                },
                {
                    "id": 14,
                    "name": "IAVAO",
                    "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IAVAO/?format=api"
                }
            ],
            "organisedByTeams": [
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                    "id": 24,
                    "name": "South Green",
                    "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api"
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            ],
            "logo_url": "",
            "updated_at": "2022-06-02T11:50:50.812642Z",
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            "event_set": [
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            ]
        },
        {
            "id": 252,
            "name": "Introduction to High-performance computing",
            "shortName": "",
            "description": "This course offers an introduction on how to work with HPC Southgreen clusters. It is intended for new users, with the goals of improving user productivity and minimizing the obstacles. The HPC Southgreen cluster are presented, together with the tools to be able to use it. Module load notion, interactive usage and batch jobs submittions will be developped.\nPrerequisites\nLinux Basics\n\nProgram\nIntroduction to HPCs architecture\nDiscover Sun grid Engine (SGE)\nData Management on clusters\nInteractive Usage\nSubmit batch jobs\n\n\nLearning objectives\nAfter this course, participants should be able to:\nUse the HPC resources interactively\nManage data copies\nUse module load\nsubmit batch jobs\n\n\nInstructors\n\n\nNdomassi Tando (NT) - ndomassi.tando@ird.fr\nBertrand Pitollat(BP) - bertrand.pitollat@cirad.fr\nAlexis Dereeper (AD) - alexis.dereeper@ird.fr​\n\n",
            "homepage": "https://southgreenplatform.github.io/trainings//HPC/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [],
            "keywords": [],
            "prerequisites": [],
            "openTo": "Internal personnel",
            "accessConditions": "",
            "maxParticipants": null,
            "contacts": [],
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                    "id": 24,
                    "name": "South Green",
                    "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api"
                }
            ],
            "logo_url": "",
            "updated_at": "2022-06-02T11:50:50.812642Z",
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                "https://catalogue.france-bioinformatique.fr/api/event/384/?format=api"
            ]
        },
        {
            "id": 347,
            "name": "Introduction to Microbial Comparative Genomics",
            "shortName": "",
            "description": "This course offers an introduction to microbial genomics analysis.\r\nIt includes 5 issues: assembly, genome annotation, circos visualization, pan-genome construction, pan-GWAS.",
            "homepage": "https://southgreenplatform.github.io/trainings//bacterialGenomics/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [],
            "keywords": [
                "genomics",
                "Structural genomics",
                "Genome analysis"
            ],
            "prerequisites": [
                "Linux - Basic Knowledge"
            ],
            "openTo": "Internal personnel",
            "accessConditions": "Open to South Green close collaborators",
            "maxParticipants": 20,
            "contacts": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/174/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/userprofile/771/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/userprofile/772/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/userprofile/773/?format=api"
            ],
            "elixirPlatforms": [],
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            "organisedByTeams": [
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                    "id": 24,
                    "name": "South Green",
                    "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api"
                }
            ],
            "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png",
            "updated_at": "2023-12-04T14:54:55.468140Z",
            "audienceTypes": [],
            "audienceRoles": [],
            "difficultyLevel": "Intermediate",
            "trainingMaterials": [],
            "learningOutcomes": "",
            "hoursPresentations": 5,
            "hoursHandsOn": 5,
            "hoursTotal": null,
            "personalised": null,
            "event_set": [
                "https://catalogue.france-bioinformatique.fr/api/event/558/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/event/561/?format=api"
            ]
        },
        {
            "id": 257,
            "name": "Metabarcoding analyses (using FROGS in Galaxy and Phyloseq)",
            "shortName": "",
            "description": "This course offers an introduction to metabarcoding analyses at two different levels/steps: bioinformatics with FROGS pipeline in the Galaxy environment, biostatistics with PhyloSeq R package. This includes preprocessing, clustering and OTU picking, taxonomic assignation, estimation of diversity, visualization of statistics results.\r\nPrerequisites\r\nGalaxy, R knowledge\r\n\r\nProgram\r\nIntroduction to metagenomics and metabarcoding\r\nPre-processing, Clustering, taxonomic affiliation (FROGS)\r\nHandling and visualizing OTU table using PhyloSeq R package (PhyloSeq)\r\n\r\n\r\nLearning objectives\r\nManipulate tools available for metabarcoding analysis\r\nStudy sample diversity by using NGS and post-NGS analysis tools\r\nVisualize diversity metrics in metabarcoding approach​\r\n\r\n\r\nInstructors\r\nJulie Orjuela - julie.orjuela@ird.fr\r\nFlorentin Constancias - florentin.constancias@cirad.fr\r\nAlexis Dereeper - alexis.dereeper@ird.fr",
            "homepage": "https://southgreenplatform.github.io/trainings//metabarcoding/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [],
            "keywords": [],
            "prerequisites": [],
            "openTo": "Internal personnel",
            "accessConditions": "Open to South Green close collaborators",
            "maxParticipants": null,
            "contacts": [],
            "elixirPlatforms": [],
            "communities": [],
            "sponsoredBy": [],
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            "organisedByTeams": [
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                    "id": 24,
                    "name": "South Green",
                    "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api"
                }
            ],
            "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png",
            "updated_at": "2023-01-24T10:25:28.170059Z",
            "audienceTypes": [],
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            "learningOutcomes": "",
            "hoursPresentations": null,
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            "event_set": [
                "https://catalogue.france-bioinformatique.fr/api/event/566/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/event/389/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/event/535/?format=api"
            ]
        },
        {
            "id": 322,
            "name": "Introduction to Structural variant detection analyses",
            "shortName": "",
            "description": "Program\r\n\r\n*  Handling mapping tools suitable for ILLUMINA and ONT data (bwa, minimap2)\r\n*  SNP detection from mapping of short reads against a reference genome: SNP calling, filters and SNP annotation. Examples of possible studies based on SNP arrays\r\n* Detecting Structural Variations (SV) in short and long reads (breakdancer, sniffle)\r\n* SV detection from genome assembly and comparison (minimap2, nucmer, assemblytics, siry)",
            "homepage": "https://southgreenplatform.github.io/trainings//sv/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [],
            "keywords": [],
            "prerequisites": [
                "Linux and knowledge of NGS formats"
            ],
            "openTo": "Internal personnel",
            "accessConditions": "Open to South Green close collaborators",
            "maxParticipants": null,
            "contacts": [],
            "elixirPlatforms": [],
            "communities": [],
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            "organisedByOrganisations": [],
            "organisedByTeams": [
                {
                    "id": 24,
                    "name": "South Green",
                    "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api"
                }
            ],
            "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png",
            "updated_at": "2023-01-24T10:41:28.470404Z",
            "audienceTypes": [],
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            "difficultyLevel": "",
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            "learningOutcomes": "",
            "hoursPresentations": 14,
            "hoursHandsOn": 14,
            "hoursTotal": 28,
            "personalised": null,
            "event_set": [
                "https://catalogue.france-bioinformatique.fr/api/event/564/?format=api"
            ]
        },
        {
            "id": 250,
            "name": "Linux For Jedi",
            "shortName": "",
            "description": "This course offers to develop and enhance advanced Linux shell command line and scripting skills for the processing and analysis of NGS data. We will work on a HPC server and use linux powerful commands to allow to analyze big amount of biological data.",
            "homepage": "https://southgreenplatform.github.io/trainings/linuxJedi/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [],
            "keywords": [],
            "prerequisites": [
                "Linux - Basic Knowledge"
            ],
            "openTo": "Internal personnel",
            "accessConditions": "Open to South Green close collaborators",
            "maxParticipants": 15,
            "contacts": [],
            "elixirPlatforms": [],
            "communities": [],
            "sponsoredBy": [],
            "organisedByOrganisations": [],
            "organisedByTeams": [
                {
                    "id": 24,
                    "name": "South Green",
                    "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api"
                }
            ],
            "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png",
            "updated_at": "2022-06-02T11:50:50.812642Z",
            "audienceTypes": [],
            "audienceRoles": [],
            "difficultyLevel": "Intermediate",
            "trainingMaterials": [],
            "learningOutcomes": "",
            "hoursPresentations": 4,
            "hoursHandsOn": 10,
            "hoursTotal": 14,
            "personalised": false,
            "event_set": [
                "https://catalogue.france-bioinformatique.fr/api/event/469/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/event/382/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/event/560/?format=api"
            ]
        },
        {
            "id": 301,
            "name": "MIAPPE, Minimum Information About Plant Phenotyping Experiments",
            "shortName": "MIAPPE",
            "description": "The Minimal Information About Plant Phenotyping Experiments (MIAPPE, www.miappe.org) standard has been designed by ELIXIR, EMPHASIS and Bioversity international to guide plant scientist in the management of experimental data. Furthermore, since genetic studies relies on the integration and the linking between phenotype and genotype datasets, relevant section of MIAPPE are beginning to be used for genotyping standards.\r\nThis formation will cover a general introduction of the MIAPPE principles and some examples to illustrate different use cases on the usage of MIAPPE for plant phenotyping data standardization.",
            "homepage": "",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [
                "http://edamontology.org/topic_3298",
                "http://edamontology.org/topic_3572",
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