Training Material List
Handles creating, reading and updating training materials.
GET /api/trainingmaterial/?format=api&offset=40&ordering=providedBy
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This is for instance the main approach to taxonomical assignments and a starting point to most diversity analyses. When exploring beyond the frontier of known biology, one should expect a large proportion of environmental sequences not exhibiting any significant similarity with known organisms. Notably, this is the case for eukaryotic viruses belonging to new families, for which the proportion of \"no match\" could reach 90%. Most metagenomics studies tend to ignore this large fraction of sequences that might be the equivalent of \"black matter\" in Biology. We will present some of the ideas and tools we are using to extract that information from large metagenomics data sets in search of truly unknown microorganisms.\nOne of the tools, \"Seqtinizer\", an interactive contig selection/inspection interface will also be presented in the context of \"pseudo-metagenomic\" projects, where the main organism under genomic study (such as sponges or corals) turns out to be (highly) mixed with an unexpected population of food, passing-by, or symbiotic microorganisms.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_3/Rational_and_tools_to_look_for_the_unknown_in_sequence_data/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-16", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/123/?format=api" ] }, { "id": 57, "name": "DNA - seq Bioinformatics Analysis", "description": "Detection of Copy Number Variations\n \n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/V07_ITMO_2016_EG_CNV.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "DNA-seq" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-11-23", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/256/?format=api" ] }, { "id": 77, "name": "Prokaryotic Phylogeny on the Fly: databases and tools for online taxonomic identification", "description": "PPF (Prokaryotic Phylogeny on the Fly) is an automated pipeline allowing to compute molecular phylogenies for prokarotic organisms. It is based on a set of specialized databases devoted to SSU rRNA, the most commonly used marker for bacterial txonomic identification. Those databases are splitted into different subsets using phylogenetic information. The procedure for computing a phylogeny is completely automated. Homologous sequence are first recruited through a BLAST search performed on a sequence (or a set of sequences). Then the homologous sequences detected are aligned using one of the multiple sequence alignment programs provided in the pipeline (MAFFT, MUSCLE or CLUSTALO). The alignment is then filtered using BMGE and a Maximum Likelihood (ML) tree is computed using the program FastTree. The tree can be rooted with an outgroup provided by the user and its leaves are coloured with a scheme related to the taxonomy of the sequences. The main advantage provided by PPF is that its databases are generated using a phylogeny-oriented procedure and and therefore much more efficient for phylogentic analyses that \"generic\" collections such as SILVA (in the case SSU rRNA) por GenBank. It is therefore much more suited to compute prokaryotic molecular phylogenies than related systems such as the Phylogeny.fr online system. PPF can be accessed online at https://umr5558-bibiserv.univ-lyon1.fr/lebibi/PPF-in.cgi\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_5/Procaryotic_phylogenu_on_the_fly/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-16", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/489/?format=api" ] }, { "id": 73, "name": "200 billion sequences and counting: analysis, discovery and exploration of datasets with EBI Metagenomics", "description": "EBI metagenomics (EMG, https://www.ebi.ac.uk/metagenomics/) is a freely available hub for the analysis and exploration of metagenomic, metatranscriptomic, amplicon and assembly data. The resource provides rich functional and taxonomic analyses of user-submitted sequences, as well as analysis of publicly available metagenomic datasets held within the European Nucleotide Archive (ENA). EMG has recently undergone rapid expansion, with an over 10-fold increase in data volumes in the first 5 months of 2016. It now houses ~ 50k publicly available data sets, and represents one of the largest collections of analysed metagenomic data. As its data content has grown, EMG has increasingly become a platform for data discovery. To support this process, we have made a series of user-interface improvements, including the classification of projects by biome, presentation of results data for better visualisation and more convenient download, and provision of project level summary files. More recently, we have indexed project metadata for use with the EBI search engine, enabling exploration across different datasets. For example, users are able to search with a particular taxonomic lineage or protein function and discover the projects, samples and sequencing runs in which that lineage or function is found. This functionality allows users to explore associations between biomes, environmental conditions and organisms and functions (e.g., discovering protein coding sequences that correspond to certain enzyme families found in aquatic environments at a given temperature range). Here, we give an overview of the EMG data analysis pipeline and web site, and illustrate the use of the new search facility for data discovery.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_7/200_billions_sequences_and_counting_discovery_and_exploration_of_datasets_with_EBI_metagenomics/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-16", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/704/?format=api" ] }, { "id": 56, "name": "RADSeq Data Analysis", "description": "Introduction to RADSeq through STACKS on Galaxy\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/V08_Yvan%20Le%20Bras%20-%20Training%20RADSeq_0.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "NGS" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-11-23", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/692/?format=api" ] }, { "id": 25, "name": "Bioconda packaging of the Regulatory Sequence Analysis Tools (RSAT)", "description": "\n \n\nBioconda packaging of the Regulatory Sequence Analysis Tools (RSAT)\n \n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/bioconda-packaging_e168/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "biohackaton 2018" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2019-03-21", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/624/?format=api" ] }, { "id": 123, "name": "IFB Cloud tutorial: Gene regulation", "description": "1. Using the Gene-regulation appliance\n1.1 Requirements\n1.2 Virtual disk creation\n1.3 Creation of an instance\n1.4 Connection to the device\n1.5 Download source data\n1.6 Execute workflow\n\n2. Visualizing results\n2.1 Install and run the X2Go client on your host computer\n2.2 Visualize results\nFastQC\nIGV\n\n\n3. Create your own Gene-regulation appliance\nCreation of an instance\nInstalling programs and dependencies\nGet the gene-regulation repository\nRun makefile to install the dependencies\n\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://github.com/rioualen/gene-regulation/blob/master/doc/gene-regulation_tutorials/gene-regulation_with_IFB_cloud.Rmd", "fileName": "missing.txt", "topics": [], "keywords": [ "Gene regulation", "Cloud Computing" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-05-31", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/660/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/624/?format=api" ] }, { "id": 13, "name": "Import workflows into TeSS Concept Maps", "description": "\n \n\nImport workflows into TeSS Concept Maps\n \n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/import-workflows-into-tess_4062/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "biohackaton 2018" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2019-03-21", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/676/?format=api" ] }, { "id": 21, "name": "Data clearinghouse, validation and curation of BioSamples - ENA - Breeding API endpoints - MAR databases", "description": "\n \n\nData clearinghouse, validation and curation of BioSamples/ENA/Breeding API endpoints/MAR databases\n \n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/data-clearinghouse_55d1/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "biohackaton 2018" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2019-03-21", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/682/?format=api" ] }, { "id": 82, "name": "Sequencing 6000 chloroplast genomes : the PhyloAlps project", "description": "Biodiversity is now commonly described by DNA based approches. Several actors are currently using DNA to describe biodiversity, and most of the time they use different genetic markers that is hampering an easy sharing of the accumulated knowledges. Taxonomists rely a lot on the DNA Barcoding initiative, phylogeneticists often prefer markers with better phylogenic properties, and ecologists, with the coming of the DNA metabarcoding, look for a third class of markers easiest to amplify from environmental DNA. Nevertheless they have all the same need of the knowledge accumulated by the others. But having different markers means that the sequecences have been got from different individuals in differente lab, following various protocoles. On that base, building a clean reference database, merging for each species all the available markers becomes a challenge. With the phyloAlps project we implement genome skimming at a large scale and propose it as a new way to set up such universal reference database usable by taxonomists, phylogeneticists, and ecologists. The Phyloalps project is producing for each species of the Alpine flora at least a genome skim composed of six millions of 100bp sequence reads. From such data it is simple to extract all chloroplastic, mitochondrial and nuclear rDNA markers commonely used. Moreover, most of the time we can get access to the complete chloroplast genome sequence and to a shallow sequencing of many nuclear genes. This methodes have already been successfully applied to algeae, insects and others animals. With the new single cell sequencing methods it will be applicable to most of the unicellular organisms. The good question is now : Can we consider the genome skimming as the next-generation DNA barcode ?\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_3/Sequencing_6000_chloroplast_genomes_the_PhyloAlps_project/scormcontent/", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-16", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/126/?format=api" ] }, { "id": 112, "name": "Chip-seq: Motif Analysis Tutorial", "description": "Introduction\nGoal\nThe aim is to :\nGet familiar with motif analysis of ChIP-seq data.\nLearn de novo motif discovery methods.\nIn practice :\nMotif discovery with peak-motifs\nDifferential analysis\nRandom controls\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://dputhier.github.io/EBA_2015_ChIP-Seq/tutorial/04_motif/motif_tutorial.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Chip-Seq", "Pattern recognition", "Motif analysis", "NGS" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": null, "maintainers": [] }, { "id": 96, "name": "Training on Galaxy : Metagenomics", "description": "Find Rapidly OTU with Galaxy Solution\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://genoweb.toulouse.inra.fr/~formation/15_FROGS/April2016/FROGS_april_2016_Formation.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics", "Galaxy" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-04-01", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/215/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/716/?format=api" ] }, { "id": 107, "name": "Genomic copy number Analysis", "description": "No description available\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/CNV_ROSCOFF_2015_BJ_20150930.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "Structural genomics", "Copy number" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2015-09-10", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/318/?format=api" ] }, { "id": 108, "name": "RNA-Seq: isoform detection and quantification", "description": "transcriptome from new condition\ntissue-speci c transcriptome\ndifferent development stages\ntranscriptome from non model organism\ncancer cell\nRNA maturation mutant\n \nHow to manage RNA-Seq data with genes subjected to di erential\nsplicing?\nIs it possible to discover new isoforms?\nIs it possible to quantify abundance of each isoform\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/toffano-TP_RNASeq_Isoform.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "Isoforms", "RNA-seq", "Transcriptomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/159/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/605/?format=api" ] }, { "id": 106, "name": "Genomic copy number Tutorial", "description": "We will analyze the copy number variations of a human tumor (parotid gland carcinoma), limited to the chr17, from a WES (whole-exome sequencing) experiment. All genomic coordinates correspond to the 2009 build of the reference human genome (hg19 / GRC37).\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/CNV_TD_guidelines_BJ.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "Structural genomics", "Copy number" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": null, "maintainers": [] } ] }