Bérénice Batut
Affiliations
Former Affiliations
Contributions
The following list includes only slides and tutorials where the individual or organisation has been added to the contributor list. This may not include the sum total of their contributions to the training materials (e.g. GTN css or design, tutorial datasets, workflow development, etc.) unless described by a news post.
19 Editorial Roles
This contributor has taken on additional responsibilities as an editor for the following topics. They are responsible for ensuring that the content is up to date, accurate, and follows GTN best practices.
- Topic: Contributing to the Galaxy Training Material
- Topic: Foundations of Data Science
- Topic: Development in Galaxy
- Topic: ELIXIR
- Topic: Microbiome
- Topic: Sequence analysis
- Topic: Teaching and Hosting Galaxy training
- Topic: Transcriptomics
- Topic: Variant Analysis
- Learning Pathway: Detection of AMR genes in bacterial genomes
- Learning Pathway: Bacterial comparative genomics
- Learning Pathway: Gallantries Grant - Intellectual Output 2 - Large-scale data analysis, and introduction to visualisation and data modelling
- Learning Pathway: Gallantries Grant - Intellectual Output 4 - Data analysis and modelling for evidence and hypothesis generation and knowledge discovery
- Learning Pathway: Gallantries Grant - Intellectual Output 5 - Train-the-Trainer and mentoring programme
- Learning Pathway: Building and Annotating Metagenome-Assembled Genomes (MAGs) from Metagenomics Reads
- Learning Pathway: Metagenomics data processing and analysis for microbiome
- Learning Pathway: Artificial Intelligence and Machine Learning in Life Sciences using Python
- Learning Pathway: Creation of a Community CoDex and lab (and optionally of a Special Interest Group (SIG))
- Learning Pathway: Train the Trainers
307 Tutorials
- Contributing to the Galaxy Training Material / Contributing with GitHub via its interface ✍️ 🧐
- Contributing to the Galaxy Training Material / Updating tool versions in a tutorial 📝 🧐
- Contributing to the Galaxy Training Material / Creating Interactive Galaxy Tours ✍️ 🧐
- Contributing to the Galaxy Training Material / Preview the GTN website as you edit your training material ✍️
- Contributing to the Galaxy Training Material / Contributing to the Galaxy Training Network with GitHub ✍️ 🧐
- Contributing to the Galaxy Training Material / Generating PDF artefacts of the website ✍️ 🧐
- Contributing to the Galaxy Training Material / Principles of learning and how they apply to training and teaching ✍️ 🧐
- Contributing to the Galaxy Training Material / Creating content in Markdown ✍️ 🧐
- Contributing to the Galaxy Training Material / Including a new topic ✍️ 🧐
- Contributing to the Galaxy Training Material / Tools, Data, and Workflows for tutorials ✍️ 🧐
- Contributing to the Galaxy Training Material / Design and plan session, course, materials ✍️ 🧐
- Contributing to the Galaxy Training Material / Adding auto-generated video to your slides 🧐
- Contributing to the Galaxy Training Material / Creating a new tutorial ✍️ 🧐
- Contributing to the Galaxy Training Material / FAIR-by-Design methodology 🧐
- Evolution / Tree thinking for tuberculosis evolution and epidemiology 🧐
- Evolution / Phylogenetic analysis for bacterial comparative genomics ✍️
- Computational chemistry / Running molecular dynamics simulations using GROMACS 🧐
- Computational chemistry / Setting up molecular systems 🧐
- Computational chemistry / Running molecular dynamics simulations using NAMD 🧐
- Computational chemistry / Analysis of molecular dynamics simulations 🧐
- Single Cell / Understanding Barcodes 🧐
- Single Cell / Downstream Single-cell RNA analysis with RaceID 🧐
- Single Cell / Clustering 3K PBMCs with Scanpy ✍️
- Single Cell / Pre-processing of 10X Single-Cell RNA Datasets 🧐
- Single Cell / Combining single cell datasets after pre-processing 🧐
- Single Cell / Pre-processing of Single-Cell RNA Data ✍️ 🧐
- Sequence analysis / Quality and contamination control in bacterial isolate using Illumina MiSeq Data ✍️ 🧐
- Sequence analysis / Quality Control ✍️ 🧐
- Sequence analysis / SARS-CoV-2 Viral Sample Alignment and Variant Visualization 🧐
- Sequence analysis / Mapping ✍️ 🧐
- Sequence analysis / Removal of human reads from SARS-CoV-2 sequencing data 🧐
- Using Galaxy and Managing your Data / Automating Galaxy workflows using the command line 🧐
- Using Galaxy and Managing your Data / Extracting Workflows from Histories 🧐
- Using Galaxy and Managing your Data / Rule Based Uploader: Advanced 🧐
- Using Galaxy and Managing your Data / Annotate, prepare tests and publish Galaxy workflows in workflow registries ✍️ 🧐
- Using Galaxy and Managing your Data / Name tags for following complex histories 🧐
- Using Galaxy and Managing your Data / Group tags for complex experimental designs 🧐
- Using Galaxy and Managing your Data / Understanding Galaxy history system 📝 🧐
- Using Galaxy and Managing your Data / Use Jupyter notebooks in Galaxy 🧐
- Using Galaxy and Managing your Data / RStudio in Galaxy ✍️ 🧐
- Using Galaxy and Managing your Data / Using dataset collections 🧐
- Using Galaxy and Managing your Data / InterMine integration with Galaxy 🧐
- Variant Analysis / Mapping and molecular identification of phenotype-causing mutations 🧐
- Variant Analysis / M. tuberculosis Variant Analysis 🧐
- Variant Analysis / Microbial Variant Calling 🧐
- Variant Analysis / Exome sequencing data analysis for diagnosing a genetic disease ✍️ 🧐
- Variant Analysis / Calling variants in diploid systems 🧐
- Variant Analysis / Calling very rare variants 🧐
- Variant Analysis / Mutation calling, viral genome reconstruction and lineage/clade assignment from SARS-CoV-2 sequencing data ✍️ 🧐
- Variant Analysis / Calling variants in non-diploid systems 🧐
- Variant Analysis / Identification of somatic and germline variants from tumor and normal sample pairs 🧐
- Visualisation / Genomic Data Visualisation with JBrowse 🧐
- Assembly / Genome Assembly of a bacterial genome (MRSA) sequenced using Illumina MiSeq Data ✍️ 🧐
- Assembly / Chloroplast genome assembly 🧐
- Assembly / Decontamination of a genome assembly 🧐
- Assembly / An Introduction to Genome Assembly 🧐
- Assembly / Unicycler assembly of SARS-CoV-2 genome with preprocessing to remove human genome reads 🧐
- Assembly / Genome Assembly Quality Control 🧐
- Assembly / Genome Assembly of MRSA from Oxford Nanopore MinION data (and optionally Illumina data) ✍️ 🧐
- Assembly / Vertebrate genome assembly using HiFi, Bionano and Hi-C data - Step by Step 🧐
- Assembly / ERGA post-assembly QC 🧐
- Assembly / Genome assembly using PacBio data 🧐
- Assembly / De Bruijn Graph Assembly 🧐
- Assembly / Assembly of the mitochondrial genome from PacBio HiFi reads 🧐
- Assembly / Making sense of a newly assembled genome 🧐
- Assembly / Using the VGP workflows to assemble a vertebrate genome with HiFi and Hi-C data 🧐
- Assembly / Unicycler Assembly 🧐
- Assembly / Large genome assembly and polishing 🧐
- Earth Data science / Functionally Assembled Terrestrial Ecosystem Simulator (FATES) 🧐
- Ecology / RAD-Seq Reference-based data analysis 🧐
- Ecology / RAD-Seq to construct genetic maps 🧐
- Ecology / Checking expected species and contamination in bacterial isolate ✍️
- Ecology / Regional GAM ✍️
- Ecology / Species distribution modeling ✍️
- Ecology / Preparing genomic data for phylogeny reconstruction 🧐
- Ecology / RAD-Seq de-novo data analysis 🧐
- Galaxy Community Building / Creation of a Galaxy tutorial table for your community ✍️ 🧐
- Galaxy Community Building / Creation of resources listing Galaxy workflow for your community ✍️ 🧐
- Galaxy Community Building / Creation of resources listing all the tools and their metadata relevant to your community ✍️ 🧐
- Galaxy Community Building / Creation of the labs in the different Galaxy instances for your community ✍️ 🧐
- Galaxy Community Building / Creating a Special Interest Group 🧐
- Galaxy Community Building / What's a Special Interest Group? 🧐
- Epigenetics / Identification of the binding sites of the T-cell acute lymphocytic leukemia protein 1 (TAL1) 🧐
- Epigenetics / Infinium Human Methylation BeadChip 🧐
- Epigenetics / Hi-C analysis of Drosophila melanogaster cells using HiCExplorer 🧐
- Epigenetics / Identification of the binding sites of the Estrogen receptor ✍️ 🧐
- Epigenetics / DNA Methylation data analysis 🧐
- Epigenetics / Formation of the Super-Structures on the Inactive X ✍️ 🧐
- Genome Annotation / Creating an Official Gene Set 🧐
- Genome Annotation / Refining Genome Annotations with Apollo (eukaryotes) 🧐
- Genome Annotation / Genome annotation with Braker3 🧐
- Genome Annotation / Bacterial genome quality control ✍️
- Genome Annotation / Genome annotation with Maker 🧐
- Genome Annotation / Essential genes detection with Transposon insertion sequencing ✍️ 🧐
- Genome Annotation / Genome annotation with Helixer 🧐
- Genome Annotation / Bacterial Genome Annotation ✍️ 🧐
- Genome Annotation / Bacterial pangenomics ✍️
- Genome Annotation / Genome annotation with Maker (short) 🧐
- Genome Annotation / Genome Annotation 🧐
- Genome Annotation / Refining Genome Annotations with Apollo (prokaryotes) 🧐
- Genome Annotation / Masking repeats with RepeatMasker 🧐
- Genome Annotation / Genome annotation with Funannotate 🧐
- Genome Annotation / Genome annotation with Prokka 🧐
- Genome Annotation / Dataset construction for bacterial comparative genomics ✍️
- Genome Annotation / Functional annotation of protein sequences 🧐
- Genome Annotation / Comparative gene analysis in unannotated genomes 🧐
- Genome Annotation / Identification of AMR genes in an assembled bacterial genome ✍️ 🧐
- Proteomics / metaQuantome 1: Data creation 🧐
- Proteomics / Detection and quantitation of N-termini (degradomics) via N-TAILS 🧐
- Proteomics / Clinical Metaproteomics 5: Data Interpretation 🧐
- Proteomics / Clinical Metaproteomics 4: Quantitation 🧐
- Proteomics / Mass spectrometry imaging: Loading and exploring MSI data 🧐
- Proteomics / Peptide and Protein Quantification via Stable Isotope Labelling (SIL) 🧐
- Proteomics / Clinical Metaproteomics 2: Discovery 🧐
- Proteomics / metaQuantome 3: Taxonomy 🧐
- Proteomics / Clinical Metaproteomics 1: Database-Generation 🧐
- Proteomics / Annotating a protein list identified by LC-MS/MS experiments 🧐
- Proteomics / Protein FASTA Database Handling 🧐
- Proteomics / Clinical Metaproteomics 3: Verification 🧐
- Proteomics / Label-free versus Labelled - How to Choose Your Quantitation Method 🧐
- Proteomics / Secretome Prediction 🧐
- Proteomics / Metaproteomics tutorial 🧐
- Proteomics / Peptide and Protein ID using OpenMS tools 🧐
- Proteomics / metaQuantome 2: Function 🧐
- Proteomics / Peptide and Protein ID using SearchGUI and PeptideShaker 🧐
- Microbiome / Taxonomic Profiling and Visualization of Metagenomic Data ✍️ 🧐
- Microbiome / Query an annotated mobile genetic element database to identify and annotate genetic elements (e.g. plasmids) in metagenomics data ✍️ 🧐
- Microbiome / Assembly of metagenomic sequencing data ✍️ 🧐
- Microbiome / Calculating α and β diversity from microbiome taxonomic data ✍️ 🧐
- Microbiome / QIIME 2 Cancer Microbiome Intervention 🧐
- Microbiome / Pathogen detection from (direct Nanopore) sequencing data using Galaxy - Foodborne Edition ✍️ 🧐
- Microbiome / 16S Microbial Analysis with mothur (short) ✍️ 🧐
- Microbiome / Analyses of metagenomics data - The global picture ✍️ 🧐
- Microbiome / QIIME 2 Moving Pictures 🧐
- Microbiome / Remove contamination and host reads ✍️
- Microbiome / Antibiotic resistance detection 🧐
- Microbiome / Identification of the micro-organisms in a beer using Nanopore sequencing ✍️ 🧐
- Microbiome / 16S Microbial Analysis with mothur (extended) ✍️ 🧐
- Microbiome / 16S Microbial analysis with Nanopore data 🧐
- Microbiome / Building and Annotating Metagenome-Assembled Genomes (MAGs) from Short Metagenomics Paired Reads ✍️ 🧐
- Microbiome / Metatranscriptomics analysis using microbiome RNA-seq data (short) ✍️ 🧐
- Microbiome / Binning of metagenomic sequencing data 📝 🧐
- Microbiome / Metatranscriptomics analysis using microbiome RNA-seq data ✍️ 🧐
- Microbiome / Building an amplicon sequence variant (ASV) table from 16S data using DADA2 ✍️ 🧐
- Teaching and Hosting Galaxy training / Teaching experiences ✍️ 🧐
- Teaching and Hosting Galaxy training / Organizing a workshop ✍️
- Teaching and Hosting Galaxy training / Teaching online ✍️
- Teaching and Hosting Galaxy training / Set up a Galaxy for Training ✍️ 🧐
- Teaching and Hosting Galaxy training / Train-the-Trainer: putting it all together ✍️ 🧐
- Teaching and Hosting Galaxy training / Galaxy Admin Training 🧐
- Teaching and Hosting Galaxy training / Assessment and feedback in training and teachings ✍️ 🧐
- Teaching and Hosting Galaxy training / Asynchronous training ✍️
- Teaching and Hosting Galaxy training / Hybrid training ✍️
- Teaching and Hosting Galaxy training / Training techniques to enhance learner participation and engagement ✍️ 🧐
- Teaching and Hosting Galaxy training / Live Coding is a Skill ✍️
- Teaching and Hosting Galaxy training / Running a workshop as an instructor ✍️
- Teaching and Hosting Galaxy training / Motivation and Demotivation ✍️ 🧐
- Introduction to Galaxy Analyses / From peaks to genes ✍️ 🧐
- Introduction to Galaxy Analyses / IGV Introduction 🧐
- Introduction to Galaxy Analyses / NGS data logistics 🧐
- Introduction to Galaxy Analyses / Upload data to Galaxy ✍️ 🧐
- Introduction to Galaxy Analyses / Galaxy Basics for everyone 🧐
- Introduction to Galaxy Analyses / Galaxy Basics for genomics 🧐
- Introduction to Galaxy Analyses / Very Short Introductions: QC 🧐
- Introduction to Galaxy Analyses / Introduction to Genomics and Galaxy 🧐
- Introduction to Galaxy Analyses / A short introduction to Galaxy 📝 🧐
- Galaxy Server administration / Deploying a compute cluster in OpenStack via Terraform 🧐
- Galaxy Server administration / Running Jobs on Remote Resources with Pulsar 🧐
- Galaxy Server administration / Reference Data with CVMFS 🧐
- Galaxy Server administration / Galaxy Database schema 🧐
- Galaxy Server administration / Galaxy Installation with Ansible 🧐
- Galaxy Server administration / Data Libraries 🧐
- Galaxy Server administration / External Authentication 🧐
- Galaxy Server administration / Ansible 🧐
- Galaxy Server administration / Distributed Object Storage 🧐
- Galaxy Server administration / Connecting Galaxy to a compute cluster 🧐
- Galaxy Server administration / Galaxy Monitoring with Reports 🧐
- Galaxy Server administration / Galaxy Monitoring with Telegraf and Grafana 🧐
- Galaxy Server administration / Galaxy Tool Management with Ephemeris 🧐
- Galaxy Server administration / Galaxy Monitoring with gxadmin 🧐
- Development in Galaxy / JavaScript plugins 🧐
- Development in Galaxy / Galaxy Webhooks 🧐
- Development in Galaxy / Data source integration ✍️ 🧐
- Development in Galaxy / Adding and updating best practice metadata for Galaxy tools using the bio.tools registry ✍️ 🧐
- Development in Galaxy / Generic plugins 🧐
- Transcriptomics / Visualization of RNA-Seq results with CummeRbund 🧐
- Transcriptomics / Reference-based RNA-Seq data analysis ✍️ 🧐
- Transcriptomics / Network analysis with Heinz 🧐
- Transcriptomics / 1: RNA-Seq reads to counts 🧐
- Transcriptomics / CLIP-Seq data analysis from pre-processing to motif detection ✍️ 🧐
- Transcriptomics / Differential abundance testing of small RNAs 🧐
- Transcriptomics / Whole transcriptome analysis of Arabidopsis thaliana 🧐
- Transcriptomics / Reference-based RNAseq data analysis (long) 🧐
- Transcriptomics / RNA Seq Counts to Viz in R ✍️ 🧐
- Transcriptomics / De novo transcriptome reconstruction with RNA-Seq 🧐
- Metabolomics / Mass spectrometry imaging: Finding differential analytes 🧐
- Metabolomics / Mass spectrometry imaging: Examining the spatial distribution of analytes 🧐
- Foundations of Data Science / R basics in Galaxy 📝 🧐
- Foundations of Data Science / One protein along the UniProt page ✍️ 🧐
- Foundations of Data Science / Advanced R in Galaxy ✍️
- Foundations of Data Science / Advanced SQL 🧐
- Foundations of Data Science / Learning about one gene across biological resources and formats ✍️ 🧐
- Foundations of Data Science / Make & Snakemake 🧐
- Foundations of Data Science / Python - Warm-up for statistics and machine learning 📝 🧐
- Statistics and machine learning / Neural networks using Python 🧐
- Statistics and machine learning / Foundational Aspects of Machine Learning using Python 📝 🧐
- Statistics and machine learning / Fine-tuning a LLM for DNA Sequence Classification ✍️ 🧐
- Statistics and machine learning / Basics of machine learning 🧐
- Statistics and machine learning / Regulations/standards for AI using DOME 📝 🧐
- Statistics and machine learning / Age prediction using machine learning 🧐
- Statistics and machine learning / Predicting Mutation Impact with Zero-shot Learning using a pretrained DNA LLM ✍️ 🧐
- Statistics and machine learning / PAPAA PI3K_OG: PanCancer Aberrant Pathway Activity Analysis 🧐
- Statistics and machine learning / Deep Learning (without Generative Artificial Intelligence) using Python 🧐
- Statistics and machine learning / Generating Artificial Yeast DNA Sequences using a DNA LLM ✍️ 🧐
- Statistics and machine learning / Machine learning: classification and regression ✍️ 🧐
- Statistics and machine learning / Interval-Wise Testing for omics data 🧐
- Statistics and machine learning / Pretraining a Large Language Model (LLM) from Scratch on DNA Sequences ✍️ 🧐
- Statistics and machine learning / Optimizing DNA Sequences for Biological Functions using a DNA LLM ✍️ 🧐
- Sequence analysis / Qualitätskontrolle ✍️
- Sequence analysis / Mapping ✍️
- Introduction to Galaxy Analyses / Von Peaks zu Genen ✍️
- Transcriptomics / Referenzbasierte RNA-Seq-Datenanalyse ✍️
- Foundations of Data Science / Ein Protein entlang der UniProt-Seite ✍️
- Foundations of Data Science / Lernen über ein Gen über biologische Ressourcen und Formate hinweg ✍️
- Sequence analysis / Control de calidad ✍️
- Sequence analysis / Mapeo ✍️
- Introduction to Galaxy Analyses / De picos a genes ✍️
- Transcriptomics / Análisis de datos RNA-Seq basados en referencias ✍️
- Foundations of Data Science / Una proteína a lo largo de la página UniProt ✍️
- Foundations of Data Science / Aprendizaje sobre un gen a través de recursos y formatos biológicos ✍️
- Sequence analysis / Controllo qualità ✍️
- Sequence analysis / Mappatura ✍️
- Introduction to Galaxy Analyses / Dai picchi ai geni ✍️
- Transcriptomics / Analisi dei dati RNA-Seq basata su riferimenti ✍️
- Foundations of Data Science / Una proteina lungo la pagina UniProt ✍️
- Foundations of Data Science / Imparare a conoscere un gene attraverso risorse e formati di dato biologici ✍️
65 Slides
- Development in Galaxy / Galaxy from a developer point of view ✍️ 🧐
- Contributing to the Galaxy Training Material / Creating Slides ✍️ 🧐
- Contributing to the Galaxy Training Material / Contributing with GitHub via command-line ✍️ 🧐
- Contributing to the Galaxy Training Material / Overview of the Galaxy Training Material ✍️ 🧐
- Sequence analysis / Quality Control ✍️ 🧐
- Sequence analysis / Mapping 🧐
- Using Galaxy and Managing your Data / Getting data into Galaxy 🧐
- Variant Analysis / Introduction to Variant analysis ✍️ 🧐
- Visualisation / Visualisations in Galaxy 🧐
- Assembly / An Introduction to Genome Assembly 🧐
- Assembly / De Bruijn Graph Assembly 🧐
- Assembly / Unicycler Assembly 🧐
- Earth Data science / Functionally Assembled Terrestrial Ecosystem Simulator (FATES) 🧐
- Earth Data science / Introduction to climate data 🧐
- Epigenetics / Introduction to DNA Methylation data analysis 🧐
- Epigenetics / Introduction to ChIP-Seq data analysis ✍️ 🧐
- Epigenetics / EWAS Epigenome-Wide Association Studies Introduction 🧐
- Epigenetics / ChIP-seq data analysis ✍️ 🧐
- Genome Annotation / Essential genes detection with Transposon insertion sequencing 🧐
- Genome Annotation / Genome annotation with Prokka 🧐
- Genome Annotation / Introduction to Genome Annotation 🧐
- Proteomics / Introduction to proteomics, protein identification, quantification and statistical modelling 🧐
- Microbiome / Introduction to Microbiome Analysis ✍️ 🧐
- Introduction to Galaxy Analyses / Options for using Galaxy 🧐
- Introduction to Galaxy Analyses / Introduction to Galaxy ✍️ 🧐
- Introduction to Galaxy Analyses / A Short Introduction to Galaxy 🧐
- Galaxy Server administration / Docker and Galaxy ✍️ 🧐
- Galaxy Server administration / Advanced customisation of a Galaxy instance 🧐
- Galaxy Server administration / Connecting Galaxy to a compute cluster 🧐
- Galaxy Server administration / User, Role, Group, Quota, and Authentication managment 🧐
- Galaxy Server administration / Server: Other 🧐
- Galaxy Server administration / Galaxy from an administrator's point of view 🧐
- Development in Galaxy / Visualizations: JavaScript Plugins 🧐
- Development in Galaxy / Scripting Galaxy using the API and BioBlend 🧐
- Development in Galaxy / Galaxy Webhooks 🧐
- Development in Galaxy / Galaxy Interactive Environments 🧐
- Development in Galaxy / Tool Dependencies and Containers 🧐
- Development in Galaxy / Galaxy Interactive Tours ✍️ 🧐
- Development in Galaxy / Tool Dependencies and Conda 🧐
- Development in Galaxy / Tool development and integration into Galaxy ✍️ 🧐
- Development in Galaxy / Tool Shed: sharing Galaxy tools ✍️ 🧐
- Development in Galaxy / Generic plugins 🧐
- Development in Galaxy / Prerequisites for building software/conda packages 🧐
- Transcriptomics / Visualization of RNA-Seq results with CummeRbund 🧐
- Transcriptomics / Introduction to Transcriptomics ✍️ 🧐
- Metabolomics / Introduction to Metabolomics 🧐
- Foundations of Data Science / Bioinformatics Data Types and Databases 🧐
- Statistics and machine learning / Neural networks using Python 🧐
- Statistics and machine learning / Regulations/standards for AI using DOME 🧐
- Statistics and machine learning / Deep Learning (without Generative Artificial Intelligence) using Python 🧐
96 FAQs
- Average Nucleotide Identity (ANI): A Measure of Genomic Similarity
- ANI threshold for dereplication
- CheckM2 vs CheckM
- How do I add my community to the Galaxy CoDex?
- Thanks!
- How can I get started with contributing?
- What is a Codex?
- Hinzufügen eines Tags ✍️
- Adding a tag
- Añadir una etiqueta ✍️
- Aggiunta di un tag ✍️
- Ändern des Datentyps ✍️
- Changing the datatype
- Modifica del tipo di dato ✍️
- Erstellen einer neuen Datei ✍️
- Creating a new file
- Creación de un nuevo fichero ✍️
- Creare un nuovo file ✍️
- Detecting the datatype (file format)
- Importieren von Daten aus einer Datenbibliothek ✍️
- Importing data from a data library
- Importar datos de una biblioteca de datos ✍️
- Importare i dati da una libreria di dati ✍️
- Importing data from repositories
- Importieren über Links ✍️
- Importing via links
- Importazione tramite link ✍️
- Umbenennen eines Datensatzes ✍️
- Renaming a dataset
- Cambiar el nombre de un conjunto de datos ✍️
- Rinominare un set di dati ✍️
- Upload few files (1-10)
- Upload many files (>10) via FTP
- The tutorial uses the normalised count table for visualisation. What about using VST normalised counts or rlog normalised counts?
- FASTQ format
- What is Galaxy?
- GTN ADR: Image Storage
- GTN ADR: Why Jekyll and not another Static Site Generator (SSG)
- GTN Architectural Decision Record Template
- What is this website?
- How can I advertise the training materials on my posters?
- What audiences are the tutorials for?
- How can I cite the GTN?
- How is the content licensed?
- Sustainability of the training-material and metadata
- What are the tutorials for?
- Kopieren eines Datensatzes zwischen Historien ✍️
- Copy a dataset between histories
- Copiar un conjunto de datos entre historiales ✍️
- Copiare un set di dati tra le cronologie ✍️
- Erstellen eines neuen Verlaufs ✍️
- Créer un nouvel history
- Creating a new history
- Para la creación de un historial nuevo ✍️
- Creare una nuova cronologia ✍️
- Importing a history
- Umbenennen eines Verlaufs ✍️
- Renaming a history
- Rinominare una cronologia ✍️
- When is the "infer experiment" tool used in practice?
- What are the best practices for teaching with Galaxy?
- What Galaxy instance should I use for my training?
- How do I get help?
- Where do I start?
- Launch RStudio
- Kraken2 and the k-mer approach for taxonomy classification
- How can I get help?
- Where do I start?
- Where can I run the hands-on tutorials?
- How do I use this material?
- Maximum MAG contamination percentage
- Minimum MAG completeness percentage
- Minimum MAG length
- Getting your API key
- Quality Scores
- Qualitätswerte ✍️
- Puntuación de calidad ✍️
- Punteggi di qualità ✍️
- Is it possible to visualize the RNA STAR bam file using the JBrowse tool?
- In 'infer experiments' I get unequal numbers, but in the IGV it looks like it is unstranded. What does this mean?
- What is Taxonomy?
- Auswählen einer Datensatzsammlung als Eingabe ✍️
- Selecting a dataset collection as input
- Selección de una colección de conjuntos de datos como entrada ✍️
- Selezione di una raccolta di dati come input ✍️
- Mehrere Datensätze auswählen ✍️
- Select multiple datasets
- Seleccionar varios conjuntos de datos ✍️
- Selezionare più insiemi di dati ✍️
- Add genome and annotations to IGV from Galaxy
- Add Mapped reads track to IGV from Galaxy
- Annotate a workflow
- Get the workflow invocation
- Importing a workflow using the Tool Registry Server (TRS) search
- Make a workflow public
- Running a workflow
18 Video Recordings
- Contributing to the Galaxy Training Material / Creating a new tutorial 🗣
- Sequence analysis / Quality Control 💬
- Genome Annotation / Bacterial Genome Annotation 💬 🗣
- Microbiome / Taxonomic Profiling and Visualization of Metagenomic Data 🗣
- Microbiome / Assembly of metagenomic sequencing data 💬 🗣
- Microbiome / Antibiotic resistance detection 💬
- Microbiome / Identification of the micro-organisms in a beer using Nanopore sequencing 🗣
- Microbiome / Building and Annotating Metagenome-Assembled Genomes (MAGs) from Short Metagenomics Paired Reads 💬 🗣
- Transcriptomics / Reference-based RNA-Seq data analysis 🗣
- Sequence analysis / Qualitätskontrolle 💬
- Transcriptomics / Referenzbasierte RNA-Seq-Datenanalyse 🗣
- Sequence analysis / Control de calidad 💬
- Transcriptomics / Análisis de datos RNA-Seq basados en referencias 🗣
- Sequence analysis / Controllo qualità 💬
- Transcriptomics / Analisi dei dati RNA-Seq basata su riferimenti 🗣
6 Events
- My Training Event Title 🧑🏫
- Galaxy Training Academy 2025 🧑🏫
- Galaxy Training Academy 2026 🧑🏫
- Galaxy Beyond Basics: Mastering Workflows, Automation, and Scalability 🎪 🧑🏫
- Galaxy Training Academy 2024 🧑🏫
Your Contributor Card
orcid Bérénice Batut
Editorial board member for Contributing to the Galaxy Training Material, Foundations of Data Science, Development in Galaxy, ELIXIR, Microbiome, Sequence analysis, Teaching and Hosting Galaxy training, Transcriptomics, Variant Analysis
307 Tutorials 96 FAQs 65 Slides Editorial Board 18 Videos 15 News 6 Events
GTN contributor since 2017-09
GitHub Activity
github Issues Reported
318 Merged Pull Requests
See all of the github Pull Requests and github Commits by Bérénice Batut.
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Fix kMetaShot assignment detail box
microbiome -
Add link for Microbiome track in GTA event schedule
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Fix loading TOC issue
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Fix URL to QIIME 2 Moving Pictures tutorial
microbiome -
[Microbiome] Add 2 modules to MAGs learning pathway
template-and-tools
Reviewed 435 PRs
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Update 2026-10-12-Advanced-Galaxy-Training.md: update registration deadline
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Fix mags-building
microbiome -
add Microbiome analysis GTA track 2026
template-and-toolsGTA -
[Microbiome] Add tutorial for MAGs building and annotation from raw reads
faqsmicrobiome -
Galaxy Formation Avancée 2026
template-and-tools
News
Next GTN CoFest May 20, 2021
New Feature: FAQs
New Tutorial: Mutation calling, viral genome reconstruction and lineage/clade assignment from SARS-CoV-2 sequencing data
New Tutorial: Pathogen detection from (direct Nanopore) sequencing data using Galaxy - Foodborne Edition
Enhancing Scientific Training: The Galaxy Training Network's Role in the ELIXIR Training Life-Cycle
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