Handles creating, reading and updating events.

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            "name": "Analyse statistique RNA-seq sous Galaxy",
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            "description": "\nObjectifs\n\nSe sensibiliser aux concepts et méthodes statistiques pour l'analyse de données transcriptomiques de type RNA-Seq.\nComprendre le matériel et méthodes (normalisation et tests statistiques) d'un article\ndu domaine.\nComprendre les particularités liées à la nature des données.\n\n \n \nProgramme\n\nPlanification expérimentale des expériences RNA-Seq (identification des biais, répétitions, biais contrôlables).\nNormalisation et analyse différentielle : recherche de \"régions d'intérêt\" différentiellement exprimées (modèle linéaire généralisé).\nPrise en compte de la multiplicité des tests.\nLe cours sera illustré par différents exemples et un jeu de données sera traité à l'aide du package R SARTools (basé sur les packages R DESeq2 et edgeR) dans les environnements Galaxy et RStudio.\n",
            "homepage": "http://migale.jouy.inra.fr/",
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            "id": 249,
            "name": "Initiation à Perl",
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            "description": "\nObjectifs\n\nInitiation à la programmation.\nIdentifier les possibilités offertes par l’écriture de quelques lignes de code.\nRéalisation de tâches simples d’extraction et de reformatage d’informations issues de fichiers texte.\n \n\n \nProgramme\n\n- Présentation de PERL\n- Variables PERL\n- Structures de contrôle\n- Gestion de fichiers\n- Réalisation de programmes simples\n \nIllustration avec des exercices de manipulation de fichiers de séquences et de fichiers de résultats d’outils bioinformatiques. \n \n",
            "homepage": "http://migale.jouy.inra.fr/",
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            "keywords": [
                "Programming Languages & Computer Sciences",
                "Perl Langage"
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            "name": "Initiation à Galaxy",
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            "name": "Infrastructure de calcul et analyses en bio-informatique",
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            "city": "Agrocampus Rennes",
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            "name": "European Galaxy Developer Workshop",
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            "name": "Data collection and registration of Diagnostic tests for Orphanet information scientists",
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            "city": "Paris (à distance)",
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            "city": "Paris, France",
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            "name": "Introduction to R Language",
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            "name": "Metagenomic amplicon analysis with stats",
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            "venue": "",
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            "name": "Analyse primaire de données issues de  séquenceurs nouvelle génération sous Galaxy",
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            "description": "\nObjectifs\n\nConnaître les concepts et méthodes bioinformatiques utilisés pour l’analyse primaire de données issues de NGS. Application aux outils de mapping et d’assemblage.\nProgramme\nThéorie \n•Présentation des différents types de séquenceurs\n•Les grandes familles d’algorithmes de mapping de lectures courtes d’assemblage et les outils associés\nPratique\nAnalyse des données de séquençage d’un génome bactérien\n•Contrôle qualité\n•Assemblage de-novo\noNettoyage des données\noAssemblage\noVisualisation et statistiques sur l’assemblage\n•Comparaison à un génome de référence :\noMapping des lectures sur un génome proche\noVisualisation du mapping \n",
            "homepage": "http://migale.jouy.inra.fr/",
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                "NGS Data Analysis",
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                "NGS Sequencing Data Analysis"
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            "accessConditions": "Ce cycle est ouvert à l'ensemble des agents de l'INRA et aux extérieurs.\n",
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            "name": "INTRODUCTION À L'ANALYSE DE DONNÉES",
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            "description": "\nL'utilisation de plus en plus répandue de techniques d’imagerie et de séquençage à haut-débit en biologie est en train de révolutionner les sciences du vivant et de modifier en profondeur leurs pratiques. Dans ce contexte, des outils statistiques sont développés pour permettre d’analyser ces données de hautes dimensions, et la maîtrise de ces outils devient de plus en plus nécessaire pour produire des résultats de bonne qualité. Ce cours de 4 semaines couvrira les étapes nécessaires pour mettre en place un processus d’analyse de données, depuis la planification de l’expérience jusqu’à la fouille des données en passant par l’échantillonnage, les test d’hypothèses, la modélisation statistique etc.\nCe cours s’adresse en priorité aux étudiants de première année de thèse de l’Institut Pasteur. Tout étudiant en thèse sera automatiquement inscrit à ce cours, mais les élèves de 2e année, de 3e année ou les post-doctorants peuvent également s’inscrire, dans la limite des places disponibles. Il est à noter que le cours est obligatoire pour les étudiants de 1ère année. Des dispenses partielles ou totales sont possibles pour les étudiants qui ont déjà des connaissances en statistique, en mathématique ou en physique. Le cours déroulera sur 4 semaines, 4 jours par semaine, trois heures par jour. Chaque séance de trois heures alternera cours magistral et mise en pratique. Il y aura deux sessions : la première commencera le 22 octobre 2018 et la deuxième le 14 janvier 2019.\nChacune de ces deux sessions sera précédée d’une séance d’introduction à l’informatique. Cette séance proposera des notions d’architecture de l’ordinateur, de système d’organisation des fichiers et de format de fichiers. Chaque session sera également suivie d’un cours optionnel sur l’analyse et le traitement des images.\nPour plus d’information, ainsi que pour les inscriptions au module optionnel et les demandes d’exemption, rendez-vous sur la page du cours : https://c3bi.pasteur.fr/introduction-to-data-analysis-2018-19/\nThèmes abordés\nLe module d’analyse de données couvrira un large champ de notions nécessaires aux étudiants pour planifier leurs expériences, analyser et explorer leurs données, interpréter les résultats et générer des figures à des fins de publication. Il abordera des notions de base en statistique, dont les analyses uni- et multivariées, les analyses descriptives, les distributions statistiques usuelles utilisées en biologie, ainsi que les tests d’hypothèses. Les exercices et travaux pratiques seront réalisés avec R et RStudio. Plusieurs séances seront consacrées à une introduction à l’utilisation du langage de programmation R avant d’aborder les notions de statistiques et d’analyse de données.\nLe module d’analyse d’images introduira les principes de base de l’analyse d’image, et portera plus particulièrement sur l’extraction d’information quantitative d’images de microscopie. Ce cours est destiné aux personnes ayant peu ou pas d’expérience en analyse d’image. Il sera très orienté sur la pratique : des cours magistraux de courte durée seront immédiatement suivis de sessions pratiques. Il aidera à la fois les microscopistes débutants et experts qui n’ont jamais eu de formation concrète en analyse d’image.\n \n\n",
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