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            "name": "Analyse de données NGS dédiée à la génomique végétale en Afrique de l'Ouest",
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            "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",
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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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            "description": "\n\n\nLes biologistes sont régulièrement confrontés à des gènes (ou des protéines) de fonctions inconnues ou mal annotés. Dans ce contexte, maîtriser quelques techniques basiques d’analyse de séquences peut se révéler d’une aide précieuse. \nL’objectif de cette formation est de présenter, au travers de l’utilisation de sites web spécialisés, quelques grands principes sur l’analyse de séquence. L’ensemble de la formation combine exposés théoriques (fondements méthodologiques des programmes) et applications pratiques (mise en relation des notions théoriques avec les paramètres des programmes et les résultats obtenus) pour permettre une utilisation autonome et critique de quelques logiciels d’analyse des séquences biologiques.\n\n\n\n",
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            "description": "L’Institut Français de Bioinformatique (IFB) organise en partenariat avec l’Institut de Biologie Intégrative de la Cellule (I2BC) une formation à destination des bioinformaticiens et biostatisticiens souhaitant mettre en oeuvre les principes “FAIR” (Facile à trouver, Accessible, Interopérable, Réutilisable) dans leurs projets d’analyse et de développement. Les concepts FAIR, initialement définis dans le contexte d’ouverture des données de la recherche, seront ici adaptés pour cadrer avec un projet type de développement et/ou analyse bioinformatique/biostatistique. Ainsi, la formation n’abordera pas les aspects “FAIR” spécifiques aux données mais introduira plusieurs outils permettant d’améliorer la reproductibilité des analyses.",
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            "description": "Bilille and ATGC organize a workshop to train users to WAVES, a Web Application for Versatile Enhanced Bioinformatic Services.",
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            "description": "Objectifs pédagogiques\r\nConnaître les concepts et méthodes bioinformatiques utilisés pour l’analyse primaire de données issues de séquenceurs nouvelle génération (NGS). Savoir effectuer un alignement sur un génome de référence, un assemblage de novo d’un génome bactérien\r\n\r\nProgramme\r\nThéorie\r\n* Présentation des différents types de technologies de séquençage (lectures longues et courtes)\r\n\r\nPratique : Analyse des données de séquençage d’un génome bactérien\r\n* Contrôle qualité\r\n* Assemblage de-novo\r\n* Nettoyage des données\r\n* Assemblage\r\n* Visualisation et statistiques sur l’assemblage\r\n* Alignement de lectures sur un génome de référence et visualisation\r\nTous les TPs seront réalisés sous l’environnement d’exécution de traitements Galaxy.",
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            "description": "Processing, statistical analysis, and annotation of metabolomics data is a complex task for experimenters since it involves many steps and requires a good knowledge of both the methodology and software tools. The Workflow4Metabolomics.org (W4M) online infrastructure provides a user-friendly and high-performance environment with advanced computational modules for building, running, and sharing complete workflows for LC-MS, GC-MS, FIA and NMR analysis. Such features are of major values for teaching computational metabolomics to experimenters, and previous courses using W4M since 2014 have been very successful.",
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            "name": "Galaxy Beyond Basics: Mastering Workflows, Automation, and Scalability",
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            "description": "Join us for an intensive, week-long, in-person training designed to elevate your Galaxy expertise to new heights. 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. 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