Training Material List
Handles creating, reading and updating training materials.
GET /api/trainingmaterial/?format=api&offset=80&ordering=fileLocation
{ "count": 144, "next": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/?format=api&limit=20&offset=100&ordering=fileLocation", "previous": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/?format=api&limit=20&offset=60&ordering=fileLocation", "results": [ { "id": 34, "name": "Users, Groups, and Quotas in Galaxy", "description": "How to handle Users, Groups, and Quotas in Galaxy\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://igbmc.github.io/egdw2017/day4/admin/08-quota-users-groups/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Galaxy" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2017-01-19", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/662/?format=api" ] }, { "id": 125, "name": "ETBII 2023", "description": "All the training materials dedicated to the IFB's Integrative Bioinformatics Thematic School, which took place in January 2023.", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://moodle.france-bioinformatique.fr/course/view.php?id=13", "fileName": "ETBII 2023 Training materials", "topics": [ "http://edamontology.org/topic_3474", "http://edamontology.org/topic_3316", "http://edamontology.org/topic_3391", "http://edamontology.org/topic_3365", "http://edamontology.org/topic_2269", "http://edamontology.org/topic_0092", "http://edamontology.org/topic_0091", "http://edamontology.org/topic_3307" ], "keywords": [ "Biological network inference and analysis", "Multivariate analyses", "Semantic web", "Data Integration" ], "audienceTypes": [ "Professional (initial)" ], "audienceRoles": [ "Life scientists", "Computer scientists", "Bioinformaticians" ], "difficultyLevel": "Novice", "providedBy": [ { "id": 29, "name": "IFB Core", "url": "https://catalogue.france-bioinformatique.fr/api/team/IFB%20Core/?format=api" } ], "dateCreation": null, "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/762/?format=api" ] }, { "id": 109, "name": "RNA-Seq: Differential Expression Analysis", "description": "\n \n\nBe careful about experimental design : avoid putting all the\nreplicates in the same lane, using the same barcode for the\nreplicates, putting different number of samples in lanes etc...\nNon- uniformity of the per base read distribution (Illumina Random\nHexamer Priming bias visible on the 13 first bases)\nBias hierarchy : biological condition >> concentration > run/flowcell> lane\nAt equivalent expression level, a long gene will have more reads than a short one.\nNon random coverage along the transcript.\nMultiple hit for some reads alignments.\n \n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://ressources.france-bioinformatique.fr/sites/default/files/EBA/V4-2015/RNAseq/billerey-roscoff_expr_diff_tp-vfinal.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "Differential Expression", "RNA-seq", "Transcriptomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/55/?format=api" ] }, { "id": 50, "name": "Welcome and Introduction", "description": "\n \n\nIntroduction message of the EGDW 2017\n \n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://ressources.france-bioinformatique.fr/sites/default/files/introduction.pdf", "fileName": " introduction.pdf", "topics": [], "keywords": [], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2017-01-16", "dateUpdate": null, "licence": null, "maintainers": [] }, { "id": 1, "name": "SG-ONT-slides", "description": "Slides used for the training \"\t\r\nIntroduction to Oxford Nanopore Technology data analyses\"", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://southgreenplatform.github.io/trainings//files/ont_2021.pdf", "fileName": "ont_2021.pdf", "topics": [], "keywords": [], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2022-01-24", "dateUpdate": "2022-01-24", "licence": "Creative Commons Attribution 4.0 International License", "maintainers": [] }, { "id": 129, "name": "Bacterial Genome Annotation", "description": "This tutorial covers the questions:\r\n- Which genes are on a draft bacterial genome?\r\n- Which other genomic components can be found on a draft bacterial genome?\r\n\r\nAt 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", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training.galaxyproject.org/training-material/topics/genome-annotation/tutorials/bacterial-genome-annotation/tutorial.html", "fileName": "bacterial-genome-annotation", "topics": [ "http://edamontology.org/topic_3301", "http://edamontology.org/topic_0219" ], "keywords": [ "Bacterial isolate", "Annotation", "Galaxy" ], "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC-BY-4.0", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ] }, { "id": 133, "name": "Introduction to image analysis using Galaxy", "description": "This tutorial covers the questions:\r\n- How do I use Galaxy with imaging data?\r\n- How do I convert images using Galaxy?\r\n- How do I display images in Galaxy?\r\n- How do I filter images in Galaxy?\r\n- How do I segment simple images in Galaxy?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- How to handle images in Galaxy.\r\n- How to perform basic image processing in Galaxy.", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training.galaxyproject.org/training-material/topics/imaging/tutorials/imaging-introduction/tutorial.html", "fileName": "imaging-introduction", "topics": [ "http://edamontology.org/topic_3383", "http://edamontology.org/topic_3382" ], "keywords": [ "Galaxy" ], "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC-BY-4.0", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ] }, { "id": 134, "name": "Nucleoli segmentation and feature extraction using CellProfiler", "description": "This tutorial covers the following questions:\r\n- How do I run an image analysis pipeline on public data using CellProfiler?\r\n- How do I analyse the DNA channel of fluorescence siRNA screens?\r\n- How do I download public image data into my history?\r\n- How do I segment and label cell nuclei?\r\n- How do I segment nucleoli (as the absence of DNA)?\r\n- How do I combine nuclei and nucleoli into one segmentation mask?\r\n- How do I extract the background of an image?\r\n- How do I relate the nucleoli to their parent nucleus?\r\n- How do I measure the image and object features?\r\n- How do I measure the image quality?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- How to download images from a public image repository.\r\n- How to segment cell nuclei using CellProfiler in Galaxy.\r\n- How to segment cell nucleoli using CellProfiler in Galaxy.\r\n- How to extract features for images, nuclei and nucleoli.", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training.galaxyproject.org/training-material/topics/imaging/tutorials/tutorial-CP/tutorial.html", "fileName": "tutorial-CP", "topics": [ "http://edamontology.org/topic_3383", "http://edamontology.org/topic_3382" ], "keywords": [ "Galaxy" ], "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC-BY-4.0", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ] }, { "id": 126, "name": "Galaxy 101 for everyone", "description": "This practical aims at familiarizing you with the Galaxy user interface. It will teach you how to perform basic tasks such as importing data, running tools, working with histories, creating workflows and sharing your work. Not everyone has the same background and that’s ok!", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training.galaxyproject.org/training-material/topics/introduction/tutorials/galaxy-intro-101-everyone/tutorial.html", "fileName": "galaxy-intro-101-everyone", "topics": [], "keywords": [], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC-BY-4.0", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ] }, { "id": 132, "name": "Metatranscriptomics analysis using microbiome RNA-seq data", "description": "This tutorial covers the questions:\r\n- How to analyze metatranscriptomics data?\r\n- What information can be extracted of metatranscriptomics data?\r\n- How to assign taxa and function to the identified sequences?\r\n\r\nAt 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", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training.galaxyproject.org/training-material/topics/microbiome/tutorials/metatranscriptomics/tutorial.html", "fileName": "metatranscriptomics", "topics": [ "http://edamontology.org/topic_1775", "http://edamontology.org/topic_3941" ], "keywords": [ "Galaxy" ], "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC-BY-4.0", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ] }, { "id": 131, "name": "16S Microbial Analysis with mothur", "description": "This tutorial covers the questions:\r\n- What is the effect of normal variation in the gut microbiome on host health?\r\n\r\nAt 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", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training.galaxyproject.org/training-material/topics/microbiome/tutorials/mothur-miseq-sop-short/tutorial.html", "fileName": "mothur-miseq-sop-short", "topics": [ "http://edamontology.org/topic_3697", "http://edamontology.org/topic_0637" ], "keywords": [ "Galaxy", "Metabarcoding" ], "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC-BY-4.0", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ] }, { "id": 130, "name": "Taxonomic Profiling and Visualization of Metagenomic Data", "description": "This tutorial covers the questions:\r\n- Which species (or genera, families, …) are present in my sample?\r\n- What are the different approaches and tools to get the community profile of my sample?\r\n- How can we visualize and compare community profiles?\r\n\r\nAt 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", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training.galaxyproject.org/training-material/topics/microbiome/tutorials/taxonomic-profiling/tutorial.html", "fileName": "taxonomic-profiling", "topics": [ "http://edamontology.org/topic_3697", "http://edamontology.org/topic_3174", "http://edamontology.org/topic_0637" ], "keywords": [ "Galaxy" ], "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC-BY-4.0", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ] }, { "id": 128, "name": "Mapping with Galaxy", "description": "This tutorial covers the questions:\r\n- What is mapping?\r\n- What two things are crucial for a correct mapping?\r\n- What is BAM?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- Define what mapping is\r\n- Perform mapping of reads on a reference genome\r\n- Evaluate the mapping output", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training.galaxyproject.org/training-material/topics/sequence-analysis/tutorials/mapping/tutorial.html", "fileName": "mapping", "topics": [ "http://edamontology.org/topic_0102" ], "keywords": [ "Mapping" ], "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC-BY-4.0", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ] }, { "id": 127, "name": "Quality Control with Galaxy", "description": "This tutorial covers the questions:\r\n- How to perform quality control of NGS raw data?\r\n- What are the quality parameters to check for a dataset?\r\n- How to improve the quality of a dataset?\r\n\r\nAt 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", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training.galaxyproject.org/training-material/topics/sequence-analysis/tutorials/quality-control/tutorial.html", "fileName": "quality-control", "topics": [ "http://edamontology.org/topic_3168", "http://edamontology.org/topic_0091" ], "keywords": [ "Quality Control" ], "audienceTypes": [ "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC-BY-4.0", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ] }, { "id": 145, "name": "Introduction to Transcriptomics", "description": "This slidedecks presents the concepts behind transcriptomics", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training.galaxyproject.org/training-material/topics/transcriptomics/tutorials/introduction/slides.html", "fileName": "transcriptomics-introduction", "topics": [ "http://edamontology.org/topic_0203", "http://edamontology.org/topic_3308", "http://edamontology.org/topic_3170" ], "keywords": [ "RNA-seq", "Transcriptomics (RNA-seq)" ], "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC-BY-4.0", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ] }, { "id": 144, "name": "Reference-based RNA-Seq data analysis with Galaxy", "description": "This tutorial covers the questions:\r\n- What are the steps to process RNA-Seq data?\r\n- How to identify differentially expressed genes across multiple experimental conditions?\r\n- What are the biological functions impacted by the differential expression of genes?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- Check a sequence quality report generated by FastQC for RNA-Seq data\r\n- Explain the principle and specificity of mapping of RNA-Seq data to an eukaryotic reference genome\r\n- Select and run a state of the art mapping tool for RNA-Seq data\r\n- Evaluate the quality of mapping results\r\n- Describe the process to estimate the library strandness\r\n- Estimate the number of reads per genes\r\n- Explain the count normalization to perform before sample comparison\r\n- Construct and run a differential gene expression analysis\r\n- Analyze the DESeq2 output to identify, annotate and visualize differentially expressed genes\r\n- Perform a gene ontology enrichment analysis\r\n- Perform and visualize an enrichment analysis for KEGG pathways", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training.galaxyproject.org/training-material/topics/transcriptomics/tutorials/ref-based/tutorial.html", "fileName": "rna-seq", "topics": [ "http://edamontology.org/topic_0102", "http://edamontology.org/topic_1775", "http://edamontology.org/topic_0203", "http://edamontology.org/topic_3308", "http://edamontology.org/topic_3170" ], "keywords": [ "Galaxy", "RNA-seq" ], "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC-BY-4.0", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ] }, { "id": 142, "name": "Introduction to python", "description": "Training slides (theory and exercises)", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training-python-for-biology-genotoul-bioinfo-a77c191514cdd1dc1b.pages.mia.inra.fr/#/title-slide", "fileName": "training-python-for-biology", "topics": [ "http://edamontology.org/topic_3316" ], "keywords": [ "Python Language" ], "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists" ], "difficultyLevel": "Novice", "providedBy": [ { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "dateCreation": null, "dateUpdate": null, "licence": "Creative Commons Attribution 4.0 International License", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/300/?format=api" ] }, { "id": 99, "name": " PASTEClassifier Tutorial", "description": "The PASTEClassifier (Pseudo Agent System for Transposable Elements Classification) is a transposable element (TE) classifier searching for structural features and similarity to classify TEs ( Hoede C. et al. 2014 )\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://urgi.versailles.inra.fr/Tools/PASTEClassifier/PASTEClassifier-tuto", "fileName": "missing.txt", "topics": [], "keywords": [ "genomics", "Transposons" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CeCILL", "maintainers": [] }, { "id": 100, "name": "REPET: TEdannot Tutorial", "description": "TEannot is able to annote a genome using DNA sequences library. This library can be a predicted TE library built by TEdenovo\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto", "fileName": "missing.txt", "topics": [], "keywords": [ "genomics", "Annotation" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CeCILL", "maintainers": [] }, { "id": 101, "name": "REPET: TEdenovo tutorial", "description": "The TEdenovo pipeline follows a philosophy in three first steps:\nDetection of repeated sequences (potential TE)\nClustering of these sequences\nGeneration of consensus sequences for each cluster, representing the ancestral TE\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://urgi.versailles.inra.fr/Tools/REPET/TEdenovo-tuto", "fileName": "missing.txt", "topics": [], "keywords": [ "genomics", "Annotation" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CeCILL", "maintainers": [] } ] }