Training List
Handles creating, reading and updating training events.
GET /api/training/?format=api&offset=120&ordering=-difficultyLevel
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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", "homepage": "http://migale.jouy.inra.fr/", "is_draft": false, "costs": [], "topics": [], "keywords": [ "NGS Data Analysis", "Metagenomics", "Galaxy" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Ce cycle est ouvert à l'ensemble des agents de l'INRA et aux extérieurs.\n", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/265/?format=api" ] }, { "id": 79, "name": "Phylogénie moléculaire", "shortName": "", "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", "homepage": "http://cnrsformation.cnrs.fr/stage-17007-Phylogenie-moleculaire-%28Montpellier%2…", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Phylogeny", "Evolution and Phylogeny", "Molecular evolution", "Speciation dating", "Selection Detection", "Supertrees and Reconciliations", "Phylogenomics", "Genes and genomes" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "S'acquitter des frais d'inscription, être familiarisé avec les banques de données de séquences, avoir déjà utilisé les logiciels de base en bioinformatique, connaître les notions de base en statistiques (tests, lois probabilistes usuelles, méthodes simples d'estimation de paramètres), avoir des notions de programmation.\n", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], 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lors de Workshop (organisation de séances de travaux pratiques)\n pour des formations individuelles\n", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Metagenomics" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Gratuit\n", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [] }, { "id": 124, "name": "Intégration d’outils dans la plateforme web GALAXY ", "shortName": "", "description": "", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Galaxy" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [] }, { "id": 76, "name": "Master Bioinfo Toulouse ", "shortName": "", "description": "Organized by Sigenae and Bioinfo Genotoul platforms.\n", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [ "Master" ], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [], 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"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": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Open to South Green close collaborators", "maxParticipants": null, "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": "2023-01-24T10:26:00.180547Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/388/?format=api" ] }, { "id": 1, "name": "Formation de base", "shortName": "", "description": "None EN\n", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "None EN\n", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/202/?format=api" ] }, { "id": 319, "name": "Exploration de la Diversité Taxonomique des Ecosystèmes par Metabarcoding", "shortName": "", "description": "En matière de prospectives scientifiques, l’INSU OA, le CNRS et l’IRD ambitionnent de caractériser la biodiversité environnementale afin d’étudier l’impact du changement global sur les milieux et de l’anthropisation de la planète. Ces enjeux nécessitent l’acquisition de connaissances sur la biodiversité pour répondre aux grands défis planétaires (e.g. modéliser, anticiper, prévenir les catastrophes écologiques), aux objectifs de développement durable, et contribuer aux grandes transitions de la société dans un contexte de changement climatique.\r\n\r\nLe metabarcoding est aujourd’hui une des approches incontournable dans la description des écosystèmes pour répondre à ces enjeux scientifiques; elle offre une caractérisation exhaustive de la diversité taxonomique (composition en espèces et abondances) d’un écosystème via le séquençage massif de marqueurs d’intérêts (e.g. ARN ribosomaux 16S, 18S, gène COX, …) et le post-traitement bio-informatique des données générées.\r\n\r\nL’Action Nationale de Formation CNRS-INSU MetaBioDiv, portée par l’Institut Méditerranéen d’Océanologie (Armougom F., MIO) et la Délégation Régionale Côte d’Azur CNRS (DR20, Pierrette Finsac), propose à la communauté scientifique une formation sur la caractérisation de la biodiversité taxonomique d’écosystèmes (procaryotes et micro-eucaryotes) par le prisme du séquençage haut-débit Illumina (Miseq) et du traitement bio-informatique associé (outils R sous Rstudio).", "homepage": "https://anfmetabiodiv.mio.osupytheas.fr", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": null, "updated_at": "2022-06-22T13:18:40.590388Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/488/?format=api" ] }, { "id": 75, "name": "Galaxy: metagenomic: sequence analysis of amplicons from MiSeq and 454 sequencing with FROGS with Galaxy first step and statistics", "shortName": "", "description": "This training session, organized by Bioinfo Genotoul, Sigenae, NED (GenPhySE) and TWB, is designed to help you to deal with NGS data of 16S, 18S ... 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