{"count":144,"next":"https://catalogue.france-bioinformatique.fr/api/trainingmaterial/?limit=20&offset=20&ordering=-dateCreation","previous":null,"results":[{"id":113,"name":"Chip Seq: Annotation and visualization Tutorial","description":"Global Objective\nGiven a set of ChIP-seq peaks annotate them in order to find associated genes, genomic categories and functional terms.\n","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"http://dputhier.github.io/EBA_2015_ChIP-Seq/tutorial/02_annotation/annotation.html","fileName":"missing.txt","topics":[],"keywords":["Chip-Seq","Data visualization","Annotation","NGS"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"","providedBy":[],"dateCreation":null,"dateUpdate":null,"licence":null,"maintainers":["https://catalogue.france-bioinformatique.fr/api/userprofile/662/","https://catalogue.france-bioinformatique.fr/api/userprofile/698/","https://catalogue.france-bioinformatique.fr/api/userprofile/644/","https://catalogue.france-bioinformatique.fr/api/userprofile/624/","https://catalogue.france-bioinformatique.fr/api/userprofile/720/","https://catalogue.france-bioinformatique.fr/api/userprofile/512/"]},{"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":94,"name":"Searching for sequence: Tutorial","description":"Quick Search is dedicated to a quick search for sequences or sequence families in the databases available on the PBIL server. It is an alternative to WWW Query which allows more complex queries. Quick Search allows you to retrieve sequences or sequence families associated to a single word without specifying what is this word. You can enter indifferently a keyword, a sequence name or accession number, or a taxa name.\n","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"http://www.prabi.fr/spip.php?article17","fileName":"missing.txt","topics":[],"keywords":["genomics","Pattern recognition"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"","providedBy":[],"dateCreation":null,"dateUpdate":null,"licence":null,"maintainers":["https://catalogue.france-bioinformatique.fr/api/userprofile/715/"]},{"id":93,"name":"Cross Taxa Tutorial","description":"How query databases according to complex taxonomic critera\nCross-Taxa allows to retrieve gene families that are shared by a given set of taxa, or which are specific to a set of taxa. It is also possible to select genes families which are associated to a certain set of taxa but which are not found in a second set of taxa. Any taxonomic level can be used.\n","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"http://www.prabi.fr/spip.php?article41","fileName":"missing.txt","topics":[],"keywords":["genomics"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"","providedBy":[],"dateCreation":null,"dateUpdate":null,"licence":null,"maintainers":["https://catalogue.france-bioinformatique.fr/api/userprofile/715/"]},{"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/"]},{"id":111,"name":"Chip-seq: Discovering motifs in peaks with RSAT","description":"Read mapping: from raw reads to aligned reads.\nPeak calling: from aligned reads to regions/peaks of high read density.\nChIP-seq annotation\nIdentification of genes related to the peaks.\nProfiles of ChIP-seq reads around reference points (TSS, histone marks,).\nFunctional enrichment of the genes related to the peaks.\n\n","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/ChIP-seq_motifs_EBA2015_JvH.pdf","fileName":"missing.txt","topics":[],"keywords":["Motif analysis","Chip Seq","NGS"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"","providedBy":[],"dateCreation":null,"dateUpdate":null,"licence":null,"maintainers":["https://catalogue.france-bioinformatique.fr/api/userprofile/624/"]},{"id":89,"name":"Docker Tutorial","description":"Docker is free software that automates the deployment of applications in software containers executant in isolation. A Docker container, away from traditional virtual machines, requires no separate operating system and not providing any but relies instead on the core functionality and uses the isolation of resources and namespaces separated to isolate the operating system as seen by the application.\n","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"http://bioserv.rpbs.univ-paris-diderot.fr/tutorials.html","fileName":"missing.txt","topics":[],"keywords":["Docker"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"","providedBy":[],"dateCreation":null,"dateUpdate":null,"licence":null,"maintainers":["https://catalogue.france-bioinformatique.fr/api/userprofile/523/"]},{"id":88,"name":"From Samples to Data : Assuring Downstream Analysis with Upstream Planning","description":"Metagenomic studies have gained increasing popularity in the years since the introduction of next generation sequencing. NGS allows for the production of millions of reads for each sample without the intermediate step of cloning. However, just as in the past, the quality of the data generate by this powerful technology depends on sample preparation, library construction and the selection of appropriate sequencing technology and sequencing depth. Here we explore the different variables involved in the process of preparing samples for sequencing analysis including sample collection, DNA extraction and library construction. We also examine the various sequencing technologies deployed for routine metagenomic analysis and considerations for their use in different model systems including humans, mouse and the environment. Future developments such as long-reads will also be discussed to provide a complete picture of important aspects prior to data analyses which play a critical role in the success of metagenomic studies.\n","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_1/From_Samples_to_Data_Assuring_Downstream_Analysis_with_Upstream_Planning/scormcontent/index.html","fileName":"missing.txt","topics":[],"keywords":["Metagenomics"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"","providedBy":[],"dateCreation":null,"dateUpdate":null,"licence":"CC BY-NC-ND","maintainers":["https://catalogue.france-bioinformatique.fr/api/userprofile/714/"]},{"id":91,"name":"A Simple Phylogenetic Tree Construction (part 1)","description":"Understand the method behind constructing a phylogenetic tree from the search for sequences to the analysis of the tree.\nGet to grips with various bio-informatic software (BLAST, CLUSTALw, SeaView and Phylo_win).\n","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"http://www.prabi.fr/spip.php?article59","fileName":"missing.txt","topics":[],"keywords":["Phylogenetics"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"","providedBy":[{"id":19,"name":"PRABI-AMSB","url":"https://catalogue.france-bioinformatique.fr/api/team/PRABI-AMSB/"}],"dateCreation":null,"dateUpdate":null,"licence":null,"maintainers":[]},{"id":92,"name":"HOVERGEN tutorial","description":"HOVERGEN is a database containing homologous vertebrate protein and nucleotide sequences. It allows to easily select similar gene sequences from a wide range of vertebrates. Hence it becomes particularly useful in comparative genomics, phylogeny and evolutionary studies on a molecular level. HOVERGEN Clean contains only complete sequences which reattach to their family. Hence its library is smaller, but more reliable.\n","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"http://www.prabi.fr/spip.php?article58","fileName":"missing.txt","topics":[],"keywords":["genomics","proteomics"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"","providedBy":[{"id":19,"name":"PRABI-AMSB","url":"https://catalogue.france-bioinformatique.fr/api/team/PRABI-AMSB/"}],"dateCreation":null,"dateUpdate":null,"licence":null,"maintainers":[]},{"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":[]},{"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/","https://catalogue.france-bioinformatique.fr/api/userprofile/605/"]},{"id":63,"name":"Variant Filtering","description":"Use cases:\nExtact a subset of variants\nCombine variants from several analysis\n\nCompare obtained variants from several data types\n\n\nIdentify new variants compare to a reference list\n\n\nApply specific filters for Chip Design\n\n","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/FiltrageVariantNLapaluRoscoff2015.pdf","fileName":"missing.txt","topics":[],"keywords":["genomics","Variant calling","NGS"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"","providedBy":[],"dateCreation":null,"dateUpdate":null,"licence":null,"maintainers":["https://catalogue.france-bioinformatique.fr/api/userprofile/694/","https://catalogue.france-bioinformatique.fr/api/userprofile/719/"]},{"id":110,"name":"DNA-seq analysis: From raw reads to processed alignments","description":"Objectives:\nMapping the DNA-seq data to the reference genome\nProcess the alignments for the variant calling\n","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/elodie_girard-itmo2015_mapping_preprocess.pdf","fileName":"missing.txt","topics":[],"keywords":["genomics","Variant calling","Alignment","DNA-seq"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"","providedBy":[],"dateCreation":null,"dateUpdate":null,"licence":null,"maintainers":["https://catalogue.france-bioinformatique.fr/api/userprofile/256/"]},{"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":49,"name":"Development in Galaxy","description":"Galaxy is an open-source project. Everyone can contribute to its development with core Galaxy development, integration of softwares in Galaxy environment, ... Here, you will find some materials to learn how to contribute to Galaxy project.\n","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"https://github.com/galaxyproject/training-material/tree/master/Dev-Corner","fileName":"missing.txt","topics":[],"keywords":["Galaxy"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"","providedBy":[],"dateCreation":null,"dateUpdate":null,"licence":null,"maintainers":["https://catalogue.france-bioinformatique.fr/api/userprofile/677/","https://catalogue.france-bioinformatique.fr/api/userprofile/77/","https://catalogue.france-bioinformatique.fr/api/userprofile/689/","https://catalogue.france-bioinformatique.fr/api/userprofile/362/"]},{"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":[]},{"id":90,"name":"A Simple Phylogenetic Tree Construction (part 2)","description":"Understand the method used in identifying an unknown sequence.\nUnderstand the limitations of this method\nGet to grips with various software (CLUSTALw, SeaView, Phylo_win and Njplot)\n","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"http://www.prabi.fr/spip.php?article60","fileName":"missing.txt","topics":[],"keywords":["Phylogenetics"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"","providedBy":[{"id":19,"name":"PRABI-AMSB","url":"https://catalogue.france-bioinformatique.fr/api/team/PRABI-AMSB/"}],"dateCreation":null,"dateUpdate":null,"licence":null,"maintainers":[]},{"id":114,"name":"Chip Seq: Annotation and visualization Lesson","description":"How to add biological meaning to peaks\n","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"http://dputhier.github.io/EBA_2015_ChIP-Seq/slides/ChIP-seq_annotation_MD_2015.pdf","fileName":"missing.txt","topics":[],"keywords":["Chip-Seq","Data visualization","Annotation","NGS"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"","providedBy":[],"dateCreation":null,"dateUpdate":null,"licence":null,"maintainers":["https://catalogue.france-bioinformatique.fr/api/userprofile/662/","https://catalogue.france-bioinformatique.fr/api/userprofile/698/","https://catalogue.france-bioinformatique.fr/api/userprofile/644/","https://catalogue.france-bioinformatique.fr/api/userprofile/624/","https://catalogue.france-bioinformatique.fr/api/userprofile/720/","https://catalogue.france-bioinformatique.fr/api/userprofile/512/"]}]}