{"count":144,"next":null,"previous":"https://catalogue.france-bioinformatique.fr/api/trainingmaterial/?limit=20&offset=120","results":[{"id":140,"name":"TP Cluster","description":"TP for cluster training (bioinfo genotoul facility)","communities":[],"elixirPlatforms":[],"doi":null,"fileLocation":"https://genotoul-bioinfo.pages.mia.inra.fr/linux-cluster/","fileName":"linux-cluster","topics":[],"keywords":["Cluster"],"audienceTypes":[],"audienceRoles":[],"difficultyLevel":"Novice","providedBy":[{"id":22,"name":"Genotoul-bioinfo","url":"https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/"}],"dateCreation":null,"dateUpdate":null,"licence":"CC BY-NC-SA","maintainers":["https://catalogue.france-bioinformatique.fr/api/userprofile/300/"]},{"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/"]},{"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/"]},{"id":146,"name":"Processing_large_files_with_sed_awk_2024","description":"This “Sed and AWK to modify large text files” training session is organized by the Genotoul bioinfo platform.\r\n\r\nThe Linux sed command is a powerful and very fast text editor without an interface. Sed can select, substitute, add, delete, and modify text in files and streams. Sed relies heavily on regular expressions for pattern matching and text selection. We’ll manipulate regexes and the sed command to modify and filter several type of file often used in bioinformatics.\r\n\r\nAWK enables to easily process columns in large text files but is also a quite powerfull programming language. This training session aims at introducing you AWK principles. You will learn about variables, operators and functions useful to manipulate very large files. \r\n\r\nFor example you can use AWK to generate your unix command lines to be launched on the cluster. AWK enables to process millions of lines in text files. 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