Training List
Handles creating, reading and updating training events.
GET /api/training/?format=api&offset=60&ordering=audienceRoles
{ "count": 391, "next": "https://catalogue.france-bioinformatique.fr/api/training/?format=api&limit=20&offset=80&ordering=audienceRoles", "previous": "https://catalogue.france-bioinformatique.fr/api/training/?format=api&limit=20&offset=40&ordering=audienceRoles", "results": [ { "id": 377, "name": "RNASEQ ALIGNMENT, QUANTIFICATION AND TRANSCRIPT DISCOVERY WITH STATISTICS", "shortName": "RNASeq bioinfo / biostat", "description": "The Toulouse Genotoul bioinformatics platform, in collaboration with the Genotoul Biostatistics platform, and the MIAT unit, organize a 3,5 days long training course for bio-informaticians and biologists aiming at learning sequence analysis. It focuses on (protein coding) gene expression analysis using reads produced by ‘RNA-Seq’. This training session is designed to introduce sequences from ‘NGS’ (Next Generation Sequencing), particularly Illumina platforms (HiSeq). You will discover the standards file formats, learn about the usual biases of this type of data and run different kinds of analyses, such as spliced alignment on a reference genome, novel gene and transcript discovery, expression quantification of coding genes and transcripts. Finally you will be able to extract the differentially expressed genes.", "homepage": "https://bioinfo.genotoul.fr/index.php/events/rnaseq-alignment-transcripts-assemblies-statistics/", "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_0203", "http://edamontology.org/topic_3308" ], "keywords": [ "NGS Data Analysis", "Expression" ], "prerequisites": [ "Linux/Unix", "Cluster", "Langage R de base" ], "openTo": "Everyone", "accessConditions": "Register on the training page : https://bioinfo.genotoul.fr/index.php/training-2/training/", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/642/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/739/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/300/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 15, "name": "MIAT", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/MIAT/?format=api" } ], "organisedByTeams": [ { "id": 33, "name": "Genotoul-biostat", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-biostat/?format=api" }, { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "logo_url": "https://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png", "updated_at": "2025-12-09T09:40:46.927545Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "Intermediate", "trainingMaterials": [ { "id": 136, "name": "Training RNASeq - biostat part - Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Training%20RNASeq%20-%20biostat%20part%20-%20Genotoul-bioinfo/?format=api" }, { "id": 135, "name": "Training RNASeq - bioinfo part - Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Training%20RNASeq%20-%20bioinfo%20part%20-%20Genotoul-bioinfo/?format=api" } ], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": 21, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/754/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/612/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/721/?format=api" ] }, { "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_0622", "http://edamontology.org/topic_0091" ], "keywords": [], "prerequisites": [ "Master" ], "openTo": "Internal personnel", "accessConditions": "The first sessions are only available for IM2B students.", "maxParticipants": 12, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [ { "id": 23, "name": "PACA-Bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/PACA-Bioinfo/?format=api" } ], "logo_url": null, "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [ "Graduate" ], "audienceRoles": [ "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 1, "hoursHandsOn": 5, "hoursTotal": 6, "personalised": null, "event_set": [] }, { "id": 363, "name": "Introduction au text-mining avec AlvisNLP", "shortName": "Introduction to text-mining with AlvisNLP", "description": "Objectifs pédagogiques\r\nCette formation est dédiée à l’analyse de données textuelles (text-mining). L’objectif est l’acquisition des principales techniques pour la Reconnaissance d’Entités Nommées (REN) à partir de textes. Les entités nommées étudiées dans cette formation sont des objets ou concepts d’intérêts mentionnés dans les articles scientifiques ou les champs en texte libre (taxons, gènes, protéines, marques, etc.).\r\n\r\nLes participants vont acquérir les compétences pratiques nécessaires pour effectuer de façon autonome une première approche pour une application de text-mining. Le format est celui de Travaux Pratiques utilisant AlvisNLP, un outil pour la création de pipelines en text-mining développé par l’équipe Bibliome de l’unité MaIAGE. La formation s’adresse à des chercheurs et ingénieurs en (bio)-informatique ou en maths-info-stats appliquées\r\n\r\nProgramme\r\n* Présentation du text-mining et de la Reconnaissance des Entités Nommées (REN)\r\n* Travaux Pratiques sur des techniques de REN en utilisant AlvisNLP\r\n* Projection de lexiques\r\n* Application de patrons\r\n* Apprentissage automatique", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_3474", "http://edamontology.org/topic_0605" ], "keywords": [ "Text mining" ], "prerequisites": [ "Linux - Basic Knowledge" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [ { "id": 10, "name": "MIGALE", "url": "https://catalogue.france-bioinformatique.fr/api/team/MIGALE/?format=api" } ], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2024-01-18T14:56:19.822106Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "Cette formation est dédiée à l’analyse de données textuelles (text-mining). L’objectif est l’acquisition des principales techniques pour la Reconnaissance d’Entités Nommées (REN) à partir de textes. Les entités nommées étudiées dans cette formation sont des objets ou concepts d’intérêts mentionnés dans les articles scientifiques ou les champs en texte libre (taxons, gènes, protéines, marques, etc.).\r\n\r\nLes participants vont acquérir les compétences pratiques nécessaires pour effectuer de façon autonome une première approche pour une application de text-mining. Le format est celui de Travaux Pratiques utilisant AlvisNLP, un outil pour la création de pipelines en text-mining développé par l’équipe Bibliome de l’unité MaIAGE. La formation s’adresse à des chercheurs et ingénieurs en (bio)-informatique ou en maths-info-stats appliquées", "hoursPresentations": 5, "hoursHandsOn": 7, "hoursTotal": 12, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/588/?format=api" ] }, { "id": 370, "name": "Introduction à l'analyse de données de métabarcoding 16S avec Galaxy", "shortName": "", "description": "L’objectif de cette formation est de se familiariser avec les étapes et les outils pour analyses de données de métabarcoding 16S. Nous proposons au personnel non-bioinformaticien de les accompagner dans la prise en main de ces étapes d’analyses en utilisant la plateforme de bio-analyse Galaxy. \r\n\r\nAprès une introduction au métabarcoding 16S, une session pratique sur la plateforme Galaxy couvrira comment :\r\n- évaluer la qualité de données de métabarcoding ,\r\n- analyser et visualiser une communauté microbienne à partir de données de métabarcoding 16S", "homepage": "", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_3697", "http://edamontology.org/topic_0637" ], "keywords": [ "Galaxy", "Metabarcoding" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Formation ouverte au personnel de l’UCA & Associés\r\nAvoir un ordinateur portable et un accès wifi eduroam\r\nAvoir un compte sur la plateforme Galaxy (Faire une demande le cas échéant sur hub.mesocentre.uca.fr)\r\nÊtre familier avec Galaxy", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/261/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 1, "name": "CNRS - IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/CNRS%20-%20IFB/?format=api" }, { "id": 16, "name": "Université Clermont Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/Universit%C3%A9%20Clermont%20Auvergne/?format=api" } ], "organisedByOrganisations": [ { "id": 87, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/AuBi/?format=api" }, { "id": 96, "name": "Mésocentre Clermont-Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/M%C3%A9socentre%20Clermont-Auvergne/?format=api" } ], "organisedByTeams": [ { "id": 31, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/team/AuBi/?format=api" } ], "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175", "updated_at": "2024-02-08T11:18:18.945136Z", "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 131, "name": "16S Microbial Analysis with mothur", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/16S%20Microbial%20Analysis%20with%20mothur/?format=api" } ], "learningOutcomes": "At the end of the tutorial, learners would be able to:\r\n- Analyze of 16S rRNA sequencing data using the mothur toolsuite in Galaxy\r\n- Using a mock community to assess the error rate of your sequencing experiment\r\n- Visualize sample diversity using Krona and Phinch", "hoursPresentations": 1, "hoursHandsOn": 2, "hoursTotal": 3, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/595/?format=api" ] }, { "id": 360, "name": "Modélisation in silico de structures 3D de protéines. Prédiction de mutations, de fixation de ligands", "shortName": "Modélisation de structures 3D de protéines", "description": "Objectifs pédagogiques\r\nA l’issue de la formation, les stagiaires connaîtront les principales fonctionnalités du logiciel PyMOL. Ils seront capables de les appliquer pour visualiser leur système biologique d’intérêt, et d’effectuer des commandes basiques d’identification de poches catalytiques, de profilage de surface électrostatique, et de mutations d’acides aminés.\r\n\r\nAussi, ils connaîtront les bases et les outils de bioinformatique structurale et seront autonomes pour effectuer des modèles de protéines par prédiction (Alphafold2), calculer les meilleures poses de fixation de leur(s) ligand(s) (Autodock4) et reconstruire l’éventuel assemblage biologique.\r\n\r\nBonus : Ils s’approprieront ces outils avec une demi-journée dédiée à la modélisation de leur système d’étude : protéines, interactions protéines/ADN, arrimage de ligand, etc.\r\n\r\nProgramme\r\nVisualiser :\r\n* Maîtriser les bases de la visualisation des protéines en 3D avec PyMOL.\r\nComprendre :\r\n* Analyser des structures 3D de protéines (RX ou RMN).\r\n* Identifier des homologues avec HHpred.\r\n* Modéliser par prédiction sa protéine d’intérêt avec Alphafold2.\r\nPrédire :\r\n* Savoir calculer des meilleures poses de ligands avec Autodock.\r\n* Prédir et modéliser les mutations in silico.\r\n\r\n- Points forts et limites des différents outils\r\n- ️“hand- on tutorials”\r\n- Plus une session dédiée : «bring your own protein»", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_1317" ], "keywords": [ "Protein structures", "2D/3D", "Protein/protein interaction modelisation" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2024-01-18T14:36:41.185563Z", "audienceTypes": [ "Professional (initial)" ], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "A l’issue de la formation, les stagiaires connaîtront les principales fonctionnalités du logiciel PyMOL. Ils seront capables de les appliquer pour visualiser leur système biologique d’intérêt, et d’effectuer des commandes basiques d’identification de poches catalytiques, de profilage de surface électrostatique, et de mutations d’acides aminés.\r\n\r\nAussi, ils connaîtront les bases et les outils de bioinformatique structurale et seront autonomes pour effectuer des modèles de protéines par prédiction (Alphafold2), calculer les meilleures poses de fixation de leur(s) ligand(s) (Autodock4) et reconstruire l’éventuel assemblage biologique.\r\n\r\nBonus : Ils s’approprieront ces outils avec une demi-journée dédiée à la modélisation de leur système d’étude : protéines, interactions protéines/ADN, arrimage de ligand, etc.", "hoursPresentations": 4, "hoursHandsOn": 8, "hoursTotal": 12, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/585/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/699/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/783/?format=api" ] }, { "id": 290, "name": "NGS data analysis on the command line", "shortName": "NGS-analysis-cli", "description": "This hands-on course will teach bioinformatic approaches for analyzing Illumina sequencing data. Our goal is to introduce the command line skills you need to make the most of your NGS data. \r\nDuring this 4-day training we will first introduce the Linux environment, shell commands and basic R scripting. And then we will focus on two NGS data analyses -- small RNA-seq and RNA-seq -- based on published datasets from the model organism Arabidopsis thaliana", "homepage": "https://www.ibmp.cnrs.fr/bioinformatics-trainings/", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_3170", "http://edamontology.org/topic_3168", "http://edamontology.org/topic_2269", "http://edamontology.org/topic_0102" ], "keywords": [], "prerequisites": [ "none" ], "openTo": "Internal personnel", "accessConditions": "This training is dedicated to academics working in a laboratory of Unistra/CNRS.", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/124/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 79, "name": "IBMP", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IBMP/?format=api" } ], "organisedByTeams": [ { "id": 14, "name": "BiGEst", "url": "https://catalogue.france-bioinformatique.fr/api/team/BiGEst/?format=api" } ], "logo_url": null, "updated_at": "2024-01-22T14:51:37.215331Z", "audienceTypes": [], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "Applied Knowledge (Know-how):\r\n- Basic proficiency at the Linux command line prompt\r\n- Basic proficiency of R (environment, objects, graphs) \r\n- Next generation sequencing (NGS) file formats; reference genomes - Mapping NGS read data to reference genomes (bowtie, samtools)\r\n- Small RNA-seq analysis; epigenomics applications (ShortStack)\r\n- RNA-seq for transcriptomics; differential gene expression analysis (HISAT2, DESeq2) - Data wrangling and visualization in R (Rstudio, ggplot2)", "hoursPresentations": 12, "hoursHandsOn": 16, "hoursTotal": 28, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/503/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/504/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/589/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/454/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/660/?format=api" ] }, { "id": 371, "name": "Introduction à l'analyse de données métatranscriptomiques avec Galaxy", "shortName": "", "description": "L’objectif de cette formation est de se familiariser avec les étapes et les outils d’analyse de données métatranscriptomiques dans le but de comprendre les fonctions d’une communauté microbienne. Nous proposons au personnel non-bioinformaticien de les accompagner dans la prise en main de ces étapes en utilisant la plateforme de bio-analyse Galaxy. \r\n\r\nAprès une introduction à la métatranscriptomique, une session pratique sur la plateforme Galaxy couvrira comment :\r\n- assigner des taxons à des données de métatranscriptomiques,\r\n- extraire des informations fonctionnelles au sein de données de métatranscriptomiques,\r\n- combiner informations taxonomiques et fonctionnelles pour faciliter la compréhension des fonctions d’une communauté microbienne", "homepage": "", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_0085", "http://edamontology.org/topic_3697", "http://edamontology.org/topic_1775", "http://edamontology.org/topic_3941" ], "keywords": [ "Galaxy" ], "prerequisites": [ "Galaxy - Basic usage" ], "openTo": "Internal personnel", "accessConditions": "Formation ouverte au personnel de l’UCA & Associés\r\nAvoir un ordinateur portable et un accès wifi eduroam\r\nAvoir un compte sur la plateforme Galaxy (Faire une demande le cas échéant sur hub.mesocentre.uca.fr)\r\nÊtre familier avec Galaxy", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/261/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 1, "name": "CNRS - IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/CNRS%20-%20IFB/?format=api" }, { "id": 16, "name": "Université Clermont Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/Universit%C3%A9%20Clermont%20Auvergne/?format=api" } ], "organisedByOrganisations": [ { "id": 87, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/AuBi/?format=api" }, { "id": 96, "name": "Mésocentre Clermont-Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/M%C3%A9socentre%20Clermont-Auvergne/?format=api" } ], "organisedByTeams": [ { "id": 31, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/team/AuBi/?format=api" } ], "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175", "updated_at": "2024-02-08T11:22:23.706233Z", "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 132, "name": "Metatranscriptomics analysis using microbiome RNA-seq data", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Metatranscriptomics%20analysis%20using%20microbiome%20RNA-seq%20data/?format=api" } ], "learningOutcomes": "At the end of the tutorial, learners would be able to:\r\n- Choose the best approach to analyze metatranscriptomics data\r\n- Understand the functional microbiome characterization using metatranscriptomic results\r\n- Understand where metatranscriptomics fits in ‘multi-omic’ analysis of microbiomes\r\n- Visualise a community structure", "hoursPresentations": 1, "hoursHandsOn": 2, "hoursTotal": 3, "personalised": null, "event_set": [] }, { "id": 362, "name": "Analyse statistique de données RNA-Seq - Recherche des régions d’intérêt différentiellement exprimées", "shortName": "Analyse statistique de données RNA-Seq", "description": "Objectifs pédagogiques\r\n* Se sensibiliser aux concepts et méthodes statistiques pour l’analyse de données transcriptomiques de type RNA-Seq.\r\n* Comprendre le matériel et méthodes (normalisation et tests statistiques) d’un article.\r\n* Réaliser une étude transcriptomique avec R dans l’environnement RStudio.\r\n\r\nProgramme\r\n* Planification expérimentale des expériences RNA-Seq (identification des biais, répétitions, biais contrôlables).\r\n* Normalisation et analyse différentielle : recherche de “régions d’intérêt” différentiellement exprimées (modèle linéaire généralisé).\r\n*Prise en compte de la multiplicité des tests.\r\n\r\nLe cours sera illustré par différents exemples. Un jeu de données à deux facteurs sera analysé avec les packages R DESeq2 et edgeR dans l’environnement RStudio.", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0203", "http://edamontology.org/topic_3170", "http://edamontology.org/topic_3308" ], "keywords": [ "Statistical differential analysis", "RNA-seq" ], "prerequisites": [ "Basic knowledge of R" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [ { "id": 10, "name": "MIGALE", "url": "https://catalogue.france-bioinformatique.fr/api/team/MIGALE/?format=api" } ], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2024-01-18T14:50:06.093352Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "Objectifs pédagogiques :\r\nSe sensibiliser aux concepts et méthodes statistiques pour l’analyse de données transcriptomiques de type RNA-Seq.\r\nComprendre le matériel et méthodes (normalisation et tests statistiques) d’un article.\r\nRéaliser une étude transcriptomique avec R dans l’environnement RStudio.", "hoursPresentations": 4, "hoursHandsOn": 8, "hoursTotal": 12, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/786/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/587/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/695/?format=api" ] }, { "id": 388, "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", "homepage": "https://bioinfo.genotoul.fr/index.php/events/analysis-of-shotgun-metagenomic-data/", "is_draft": false, "costs": [ "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" ], "topics": [ "http://edamontology.org/topic_3174" ], "keywords": [ "NGS Data Analysis", "Metagenomics" ], "prerequisites": [ "Linux/Unix", "Cluster" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/300/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" }, { "id": 37, "name": "MIAT - Mathématiques et Informatique Appliquées de Toulouse", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/MIAT%20-%20Math%C3%A9matiques%20et%20Informatique%20Appliqu%C3%A9es%20de%20Toulouse/?format=api" } ], "organisedByTeams": [ { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "logo_url": "https://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png", "updated_at": "2026-03-02T08:49:21.302798Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "Intermediate", "trainingMaterials": [ { "id": 151, "name": "Metagenomic training - Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Metagenomic%20training%20-%20Genotoul-bioinfo/?format=api" } ], "learningOutcomes": "", "hoursPresentations": 3, "hoursHandsOn": 15, "hoursTotal": 18, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/670/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/758/?format=api" ] }, { "id": 412, "name": "Construction and analysis of eukaryotic pangenome graphs", "shortName": "", "description": "This training session is organized by the Genotoul-Bioinfo platform. This 2 days long course is dedicated to the construction and the analysis of eukaryotic pangenome graphs.\r\n\r\nWe will first present the concept of graph-based pangenome, then build one. We will then apply several tools for its analysis: use annotation, call variants, extract sub-graphs, visualize the graph, map reads, genotype individuals, and perform a GWAS on the graph. The different formats will also be presented.\r\n\r\nBy the end of the course, trainees will be familiar with the topic, and able to run the major tools made to build an exploit a pangenome graph.", "homepage": "https://bioinfo.genotoul.fr/index.php/events/pangenome/", "is_draft": false, "costs": [ "Non-academic for non-academic: 1100€ + 20% taxes (TVA)", "INRAE for INRAE's staff: 300 € no VAT charged", "Academic non-INRAE for academic but non-INRAE: 340 € + 20% taxes (TVA)" ], "topics": [ "http://edamontology.org/topic_3796", "http://edamontology.org/topic_0625" ], "keywords": [ "Pangenomic" ], "prerequisites": [ "Linux/Unix", "Cluster" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/642/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" }, { "id": 37, "name": "MIAT - Mathématiques et Informatique Appliquées de Toulouse", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/MIAT%20-%20Math%C3%A9matiques%20et%20Informatique%20Appliqu%C3%A9es%20de%20Toulouse/?format=api" } ], "organisedByTeams": [ { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "logo_url": "https://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png", "updated_at": "2026-04-20T08:06:46.497837Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 3, "hoursHandsOn": 15, "hoursTotal": 18, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/799/?format=api" ] }, { "id": 367, "name": "Introduction à l'analyse de données de séquençage avec contrôle qualité et alignement sur un génome de référence avec Galaxy", "shortName": "", "description": "L’objectif de cette formation est de se familiariser avec les premières étapes communes à toutes les analyses de données de séquençage : le contrôle qualité des données et l’alignement sur un génome de référence. Nous proposons au personnel non-bioinformaticien de les accompagner dans la prise en main des ces étapes d’analyses en utilisant la plateforme de bio-analyse Galaxy. \r\n\r\nAprès une introduction aux données de séquençage, une session pratique sur la plateforme Galaxy couvrira comment :\r\n- évaluer la qualité de données de séquençage,\r\n- améliorer la qualité de données de séquençage\r\n- aligner des données sur un génome de référence", "homepage": "", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_0091", "http://edamontology.org/topic_0102" ], "keywords": [ "Quality Control", "Galaxy", "Mapping" ], "prerequisites": [ "Galaxy - Basic usage" ], "openTo": "Internal personnel", "accessConditions": "Formation ouverte au personnel de l’UCA & Associés\r\nAvoir un ordinateur portable et un accès wifi eduroam\r\nAvoir un compte sur la plateforme Galaxy (Faire une demande le cas échéant sur hub.mesocentre.uca.fr)\r\nÊtre familier avec Galaxy", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/261/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 1, "name": "CNRS - IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/CNRS%20-%20IFB/?format=api" }, { "id": 16, "name": "Université Clermont Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/Universit%C3%A9%20Clermont%20Auvergne/?format=api" } ], "organisedByOrganisations": [ { "id": 87, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/AuBi/?format=api" }, { "id": 96, "name": "Mésocentre Clermont-Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/M%C3%A9socentre%20Clermont-Auvergne/?format=api" } ], "organisedByTeams": [ { "id": 31, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/team/AuBi/?format=api" } ], "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175", "updated_at": "2024-02-08T11:22:59.733596Z", "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 128, "name": "Mapping with Galaxy", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Mapping%20with%20Galaxy/?format=api" }, { "id": 127, "name": "Quality Control with Galaxy", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Quality%20Control%20with%20Galaxy/?format=api" } ], "learningOutcomes": "At the end of the tutorial, learners would be able to:\r\n- Assess short reads FASTQ quality using FASTQE 🧬😎 and FastQC\r\n- Assess long reads FASTQ quality using Nanoplot and PycoQC\r\n- Perform quality correction with Cutadapt (short reads)\r\n- Summarise quality metrics MultiQC\r\n- Process single-end and paired-end data\r\n- Define what mapping is\r\n- Perform mapping of reads on a reference genome\r\n- Evaluate the mapping output", "hoursPresentations": 1, "hoursHandsOn": 2, "hoursTotal": 3, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/593/?format=api" ] }, { "id": 279, "name": "Annotation and analysis of prokaryotic genomes using the MicroScope platform", "shortName": "MicroScope training", "description": "In an effort to inform members of the research community about our annotation methods, to provide training for collaborators and other scientists who use the MicroScope platfom, and to inform scientific public on the analysis available in PkGDB (Prokaryotic Genome DataBase), we have developed a 4.5-day course in Microbial Genome Annotation and Comparative Analysis using the MaGe graphical interfaces.\r\n\r\nThis course will familiarize attendees with LABGeM’s annotation pipeline and the manual annotation software MaGe (Magnifying Genome) . No specific bioinformatics skill is required: detailed instruction on the algorithm developed in each annotation methods can be found in specific training courses on «Genomic sequences analysis». Here we focus on the general idea behind each method and, above all, the way you can interpret the corresponding results and combine them with other evidences in order to change or correct the current automatic functional annotation of a given gene, if necessary.\r\n\r\nThis course will also describe how to perform effective searches and analysis of procaryotic data using the graphical functionalities of the MaGe’s interfaces. Because of the numerous pre-computation available in our system (results of “common” annotation tools, synteny with all complete bacterial genomes, metabolic pathway reconstruction, fusion/fission events, genomic islands, …), many practical exercises allow attendees to get familiar with the use the MaGe graphical interfaces in order to efficiently explore these sets of results.", "homepage": "https://labgem.genoscope.cns.fr/professional-trainings/microscope-professional-trainings/training-annotation-analysis-of-prokaryotic-genomes-using-the-microscope-platform/", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0085", "http://edamontology.org/topic_3301", "http://edamontology.org/topic_0797" ], "keywords": [], "prerequisites": [ "Licence" ], "openTo": "Everyone", "accessConditions": "External training sessions can also be scheduled on demand, in France or abroad. See : https://labgem.genoscope.cns.fr/professional-trainings/microscope-professional-trainings/external-microscope-professional-training-sessions/", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/90/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 15, "name": "Laboratory of Bioinformatics Analyses for Genomics and Metabolism", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/Laboratory%20of%20Bioinformatics%20Analyses%20for%20Genomics%20and%20Metabolism/?format=api" } ], "organisedByOrganisations": [ { "id": 67, "name": "University Paris-Saclay", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/University%20Paris-Saclay/?format=api" } ], "organisedByTeams": [ { "id": 9, "name": "MicroScope", "url": "https://catalogue.france-bioinformatique.fr/api/team/MicroScope/?format=api" } ], "logo_url": "https://labgem.genoscope.cns.fr/wp-content/uploads/2019/06/MicroScope_logo-300x210.png", "updated_at": "2025-12-09T09:10:02.012461Z", "audienceTypes": [ "Undergraduate", "Graduate", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists", "Curators" ], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "Annotation and comparative analysis of bacterial genomes:\r\n\r\n- acquire theoretical and practical knowledge of genome annotation tools (structural and functional annotation, metabolic networks annotation)\r\n- interpret the results of functional annotation tools\r\nperform various comparative analyses : conserved synteny analyses, pan-genome, phylogenetic and metabolic profiles.\r\n- analyse the results of metabolic networks prediction tools and look for candidate genes for enzyme activities.\r\n- use the tools to analyse the genome(s) of interest of participants", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": 31, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/439/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/506/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/436/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/745/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/507/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/577/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/576/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/659/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/658/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/796/?format=api" ] }, { "id": 368, "name": "Introduction à l'annotation de génomes bactériens avec Galaxy", "shortName": "", "description": "L’objectif est cette formation de se familiariser avec les étapes et les outils pour annoter des génomes bactériens. Nous proposons au personnel non-bioinformaticien de les accompagner dans la prise en main de l’annotation de génomes bactériens en utilisant la plateforme de bio-analyse Galaxy. \r\n\r\nAprès une introduction à l’annotation de génomes bactériens, une session pratique sur la plateforme Galaxy couvrira comment :\r\n- faire tourner une série d’outils pour annoter un génome bactérien avec différents éléments génomiques,\r\n- évaluer l’annotation\r\n- visualiser un génome bactérien et ses annotations", "homepage": "", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_3301", "http://edamontology.org/topic_0097", "http://edamontology.org/topic_0622", "http://edamontology.org/topic_0219" ], "keywords": [ "Bacterial isolate", "Galaxy", "Structural and functional annotation of genomes" ], "prerequisites": [ "Galaxy - Basic usage" ], "openTo": "Internal personnel", "accessConditions": "Formation ouverte au personnel de l’UCA & Associés\r\nAvoir un ordinateur portable et un accès wifi eduroam\r\nAvoir un compte sur la plateforme Galaxy (Faire une demande le cas échéant sur hub.mesocentre.uca.fr)\r\nÊtre familier avec Galaxy", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/261/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 1, "name": "CNRS - IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/CNRS%20-%20IFB/?format=api" }, { "id": 16, "name": "Université Clermont Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/Universit%C3%A9%20Clermont%20Auvergne/?format=api" } ], "organisedByOrganisations": [ { "id": 87, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/AuBi/?format=api" }, { "id": 96, "name": "Mésocentre Clermont-Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/M%C3%A9socentre%20Clermont-Auvergne/?format=api" } ], "organisedByTeams": [ { "id": 31, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/team/AuBi/?format=api" } ], "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175", "updated_at": "2024-02-08T11:22:51.682232Z", "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 129, "name": "Bacterial Genome Annotation", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Bacterial%20Genome%20Annotation/?format=api" } ], "learningOutcomes": "At the end of the tutorial, learners would be able to:\r\n- Run a series of tools to annotate a draft bacterial genome for different types of genomic components\r\n- Evaluate the annotation\r\n- Process the outputs to format them for visualization needs\r\n- Visualize a draft bacterial genome and its annotations", "hoursPresentations": 1, "hoursHandsOn": 2, "hoursTotal": 3, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/598/?format=api" ] }, { "id": 288, "name": "Introduction to the command-line interface", "shortName": "BirdLinux", "description": "Objectives\r\n- Understand the principles and advantages of the Linux system\r\n- Know and use the main bash commands.\r\n- Ability to chain multiple commands using pipes\r\n- Launch programs with arguments\r\n- Gain independence to perform command line analyses\r\n\r\nCourse Content\r\n- Introduction to the Linux system.\r\n- File system: directory structure, paths, home directory, file and directory management.\r\n- Principle of protections: reading file attributes, access rights, management of user groups.\r\n- Useful commands for file manipulation\r\n- Redirection operators (command input/output)\r\n- Creating and running a bash script\r\nIntroduction to environment variables\r\nConnecting to a remote server via a terminal or via WSL", "homepage": "https://pf-bird.univ-nantes.fr/training/linux/", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0605" ], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 20, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/596/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [ { "id": 16, "name": "BiRD", "url": "https://catalogue.france-bioinformatique.fr/api/team/BiRD/?format=api" } ], "logo_url": "https://bird.univ-nantes.io/website/images/logo/logo.svg", "updated_at": "2026-03-02T16:28:48.048808Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 1, "hoursHandsOn": 6, "hoursTotal": 7, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/601/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/639/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/747/?format=api" ] }, { "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" ], "topics": [ "http://edamontology.org/topic_3673", "http://edamontology.org/topic_3168", "http://edamontology.org/topic_0196" ], "keywords": [], "prerequisites": [ "Linux and knowledge of NGS formats" ], "openTo": "Everyone", "accessConditions": "", "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": "2023-01-24T10:21:58.467251Z", "audienceTypes": [ "Professional (initial)" ], "audienceRoles": [ "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 1, "name": "SG-ONT-slides", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/SG-ONT-slides/?format=api" } ], "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, "hoursTotal": 12, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/441/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/450/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/562/?format=api" ] }, { "id": 344, "name": "Analyses Single Cell RNA-seq (ScRNA-seq) avec R", "shortName": "", "description": "Cette formation introduira notamment la librairie Seurat permettant la manipulation et l'analyse de données Single Cell RNA-seq ainsi que la visualisation des résultats d'analyse\r\n\r\n- Rappels des concepts du séquençage Single Cell RNA-seq\r\n- Importation des données Single Cell dans R\r\n- Intégration de données Single Cell multiples\r\n- Quality Check et pré-traitement des données\r\n- Normalisation de données\r\n- Identification de marqueurs\r\n- Clustering et assignation cellulaire\r\n- Analyse différentielle des groupes cellulaires\r\n- Savoir intégrer les données de spatialisation\r\n- Savoir intégrer les données de trajectoire\r\n- Savoir intégrer les données de communication cellulaire\r\n- Savoir intégrer les données d'épigénétique (ATAC-seq)", "homepage": "https://cnrsformation.cnrs.fr/analyses-single-cell-rna-seq-scrna-seq-avec-r?axe=176", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Bioinformatics & Biomedical", "R Language", "R", "NGS Sequencing Data Analysis" ], "prerequisites": [ "Basic knowledge of R", "R programming" ], "openTo": "Everyone", "accessConditions": "Maîtrise du langage R\r\nAvoir suivi le stage \"Langage R : introduction\" ou niveau équivalent.\r\nAfin de vérifier que votre maîtrise du langage R est suffisante pour pouvoir suivre ce stage, nous vous invitons à effectuer et à renvoyer le test téléchargeable\r\nhttps://cnrsformation.cnrs.fr/data/STG_23294_55153.docx", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/154/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 6, "name": "CNRS formation entreprise", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/CNRS%20formation%20entreprise/?format=api" } ], "organisedByOrganisations": [ { "id": 1, "name": "CNRS formation entreprises", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/CNRS%20formation%20entreprises/?format=api" } ], "organisedByTeams": [ { "id": 6, "name": "CBiB", "url": "https://catalogue.france-bioinformatique.fr/api/team/CBiB/?format=api" } ], "logo_url": "https://services.cbib.u-bordeaux.fr/utils/logo_cbib.png", "updated_at": "2023-08-31T09:19:56.754683Z", "audienceTypes": [ "Graduate", "Professional (initial)" ], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "- Savoir expertiser et manipuler des données issues d'expériences Single Cell RNA-seq\r\n- Savoir mener une analyse différentielle à de multiples niveaux\r\n- Savoir intégrer des données complémentaires pour l'analyse Single Cell RNA-seq (spatial, trajectoire, cell communication, cell identification...)", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/650/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/653/?format=api" ] }, { "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" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/344/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/739/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 37, "name": "MIAT - Mathématiques et Informatique Appliquées de Toulouse", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/MIAT%20-%20Math%C3%A9matiques%20et%20Informatique%20Appliqu%C3%A9es%20de%20Toulouse/?format=api" } ], "organisedByTeams": [ { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "logo_url": "https://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png", "updated_at": "2025-12-09T09:42:16.231660Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 137, "name": "Linux slides - Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Linux%20slides%20-%20Genotoul-bioinfo/?format=api" }, { "id": 138, "name": "Linux TP - Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Linux%20TP%20-%20Genotoul-bioinfo/?format=api" } ], "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.", "hoursPresentations": 3, "hoursHandsOn": 3, "hoursTotal": 6, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/476/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/608/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/447/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/667/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/752/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/632/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/528/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/719/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/800/?format=api" ] }, { "id": 369, "name": "Introduction au profilage taxonomique et visualisation de communautés microbiennes à partir de données métagénomiques avec Galaxy", "shortName": "", "description": "L’objectif de cette formation est de se familiariser avec les étapes et les outils d’analyse de données de métagénomiques pour caractériser et visualiser des communautés microbiennes. Nous proposons au personnel non-bioinformaticien de les accompagner dans la prise en main de ces étapes en utilisant la plateforme de bio-analyse Galaxy. \r\n\r\nAprès une introduction à la métagénomique, une session pratique sur la plateforme Galaxy couvrira comment :\r\n- assigner des taxons à des données de métagénomiques,\r\n- visualiser une communauté microbienne à partir d’assignations taxonomiques", "homepage": "", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_3697", "http://edamontology.org/topic_3174", "http://edamontology.org/topic_0637" ], "keywords": [ "Galaxy" ], "prerequisites": [ "Galaxy - Basic usage" ], "openTo": "Internal personnel", "accessConditions": "Formation ouverte au personnel de l’UCA & Associés\r\nAvoir un ordinateur portable et un accès wifi eduroam\r\nAvoir un compte sur la plateforme Galaxy (Faire une demande le cas échéant sur hub.mesocentre.uca.fr)\r\nÊtre familier avec Galaxy", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/261/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 1, "name": "CNRS - IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/CNRS%20-%20IFB/?format=api" }, { "id": 16, "name": "Université Clermont Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/Universit%C3%A9%20Clermont%20Auvergne/?format=api" } ], "organisedByOrganisations": [ { "id": 87, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/AuBi/?format=api" }, { "id": 96, "name": "Mésocentre Clermont-Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/M%C3%A9socentre%20Clermont-Auvergne/?format=api" } ], "organisedByTeams": [ { "id": 31, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/team/AuBi/?format=api" } ], "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175", "updated_at": "2024-02-08T11:23:11.090144Z", "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 130, "name": "Taxonomic Profiling and Visualization of Metagenomic Data", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Taxonomic%20Profiling%20and%20Visualization%20of%20Metagenomic%20Data/?format=api" } ], "learningOutcomes": "At the end of the tutorial, learners would be able to:\r\n- Explain what taxonomic assignment is\r\n- Explain how taxonomic assignment works\r\n- Apply Kraken and MetaPhlAn to assign taxonomic labels\r\n- Apply Krona and Pavian to visualize results of assignment and understand the output\r\n- Identify taxonomic classification tool that fits best depending on their data", "hoursPresentations": 1, "hoursHandsOn": 2, "hoursTotal": 3, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/599/?format=api" ] }, { "id": 375, "name": "RNASeq Analysis", "shortName": "RNASeq Analysis", "description": "Objectives\r\n- Understand the key steps in RNASeq data analysis for a differential expression study\r\n- Know how to perform command-line analysis using Snakemake.\r\n\r\nPedagogical Content\r\nDay 1\r\n- Principle of RNASeq technology: objectives and experimental design.\r\n- Data quality assessment (FastQC, MultiQC).\r\n- Sequence alignment to a reference genome (STAR).\r\n\r\nDay 2\r\n- Differential gene expression analysis (HTSeqCount, DESeq2).\r\n- Functional annotation (GO, Kegg).\r\n- Using the Snakemake workflow system.\r\n- Comparison between RNASeq and 3’SRP methods.\r\n\r\nThe theoretical part is followed by a pipeline run step-by-step on a test dataset. \r\nIt will be possible to start an analysis on your own data.", "homepage": "https://pf-bird.univ-nantes.fr/training/rnaseq/", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "- Be comfortable with basic Linux commands or have completed the training course “Introduction to the command-line interface.”\r\n- Be familiar with the use of a computing cluster, conda/mamba et snakemake or have completed the training course “Best practices in bioinformatics.”", "maxParticipants": 12, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [ { "id": 16, "name": "BiRD", "url": "https://catalogue.france-bioinformatique.fr/api/team/BiRD/?format=api" } ], "logo_url": "https://bird.univ-nantes.io/website/images/logo/logo.svg", "updated_at": "2026-03-02T16:30:29.225935Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 7, "hoursHandsOn": 7, "hoursTotal": 14, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/746/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/603/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/640/?format=api" ] }, { "id": 275, "name": "Single-Cell : Transcriptomics, Spatial and Long reads", "shortName": "SincellTE", "description": "This workshop focuses on the large-scale study of heterogeneity across individual cells from a genomic, transcriptomic and epigenomic point of view. New technological developments enable the characterization of molecular information at a single cell resolution for large numbers of cells. The high dimensional omics data that these technologies produce raise novel methodological challenges for the analysis. In this regard, dedicated bioinformatics and statistical methods have been developed in order to extract robust information.\r\n\r\nThe workshop aims to provide such methods for engineers and researchers directly involved in functional genomics projects making use of single-cell technologies. A wide range of single cell topics will be covered in lectures, demonstrations and practical classes. Among others, the areas and issues to be addressed will include the choice of the most appropriate single-cell sequencing technology, the experimental design and the bioinformatics and statistical methods and pipelines. For this edition, new courses/practicals will focus on spatial transcriptomics, cell phenotyping and additional multi-omics.\r\n\r\nA wide range of single cell topics will be covered in lectures, demonstrations and practical classes. Among others, the areas and issues to be addressed will include the choice of the most appropriate single-cell sequencing technology, the experimental design and the bioinformatics and statistical methods and pipelines. For this edition, new courses/practicals will focus on spatial transcriptomics, cell phenotyping and additional multi-omics.\r\n\r\nRequirements : Participants must have prior experience on NGS data analysis with everyday use of R and good knowledge of Unix command line. Before the training, participants will be asked to familiarize themselves with the processing and primary analyses steps of scRNA-seq datasets with provided pedagogic material.\r\n\r\nIt is not necessary to have personal single-cell data to analyse.", "homepage": "", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [], "prerequisites": [ "Master", "Autre (Diplôme universitaire, école d'ingénieur ...)" ], "openTo": "Everyone", "accessConditions": "Participants must have prior experience on NGS data analysis with everyday use of R and/or Python and good knowledge of Unix command line. 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