Handles creating, reading and updating training events.

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                "Comparative and de novo structure modeling",
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            "name": "Phylogénie moléculaire",
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            "description": "\nLes objectifs sont :\n1. Acquérir des connaissances théoriques et pratiques en phylogénie moléculaire.\n2. Être autonome dans la conduite d'une analyse phylogénétique.\n3. Maîtriser le choix, le paramétrage et l'exploitation des résultats des programmes de phylogénie.\nhttps://cnrsformation.cnrs.fr/\n\n",
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                "Evolution and Phylogeny",
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            "name": "Cycle « Analyse de données de séquençage à haut-débit » - Module 2/5 : Analyses de variants",
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            "description": "Bilille propose chaque année un cycle de formation d'introduction à l'analyse des données de séquençage à haut débit.\r\nCe cycle est composé de 5 modules, à la carte : \r\n- Module 1: Analyses ADN\r\n- Module 2: Analyses de variants\r\n- Module 3: Analyses RNA-seq, bioinformatique\r\n- Module 4: Analyses RNA-seq, biostatistique\r\n- Module 5: Métagénomique\r\nLes fiches descriptives sont accessibles sur le site de Bilille. Chaque module comprend des présentations générales et des séances pratiques sur ordinateur, avec Galaxy.\r\nLes objectifs du module 2 sont :\r\n- Comprendre les grands principes de la détection de variants\r\n- Réaliser les différentes étapes du post-traitement des données d’alignement à la détection de variants\r\n- Adapter l’analyse en fonction du type de données NGS générées\r\n- Comprendre la structure des données de variants\r\n- Savoir annoter des variants\r\n- Etre capable d’interpréter une liste de variants grâce aux outils libres disponibles",
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            "name": "Traitement des données NGS sous Galaxy",
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            "id": 33,
            "name": "Analyse statistique RNA-seq sous Galaxy",
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            "description": "Licence 2 bioinformatique appliquée (Van Helden J)\n",
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            "name": "Analyse de données métagénomiques 16S",
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            "description": "\n\n\n\n\n\n\n\nObjectifs\nCette formation est dédiée à l'analyse de données de type \"métagénomique amplicon\" issues des technolo-gies de séquençage 454 et Illumina. La formation couvre les grandes étapes d'un pipeline d'analyse bioinformatique sous Galaxy (FROGS) pour transformer les séquences en tables d'abondances puis présente des outils statistiques sous R (phyloseq) qui permettent de décrire et comparer les échantillons à partir de ces tables.\n\n \nProgramme\n\nJours 1 et 2 : Analyses Bioinformatiques sous Galaxy\nIntroduction générale\nBrefs rappels sur l'environnement Galaxy\nPrésentation des données issues des différentes technologies de séquençage\nPrétraitement des données\nClustering des séquences, construction des OTUs\nDétection de chimères\nAnnotation taxonomique\nFiltrage des données de comptages\nOutils de visualisation\nConstruction de workflow et configuration de FROGS\nLimite des données et des méthodes \nJour 3 et 4 :  Analyses Statistiques sous Rstudio\nIntroduction générale\nImport, manipulation et visualisation des données\nMesure de diversités : Unifrac, Bray-Curtis, etc.\nOrdination et réduction de dimension : MDS\nClustering et Heatmap\nComparaison d'échantillons : PERMANOVA, adonis\n▫ Introduction générale\n▫ Brefs rappels sur l'environnement Galaxy\n▫ Présentation des données issues des différentes technologies de séquençage ▫ Prétraitement des données\n▫ Clustering des séquences, construction des OTUs\n▫ Détection de chimères\n▫ Annotation taxonomique\n▫ Filtrage des données de comptages\n▫ Outils de visualisation\n▫ Construction de workflow et configuration de FROGS\n▫ Limite des données et des méthodes\n\n\n\n\n\nJour 3 : Analyses Statistiques sous Rstudio\n\n\t▫  Introduction générale\n\t\n\n\t▫  Import et manipulation des données\n\t\n\n\t▫  Mesure de diversités : Unifrac, Bray-Curtis, etc.\n\t\n\n\t▫  Ordination et réduction de dimension : MDS\n\t\n\n\t▫  Clustering et Heatmap\n\t\n\n\t▫  Comparaison d'échantillons : PERMANOVA, adonis \n\t\n\n\n\n\n\n\n\n\n",
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