Björn Grüning
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.
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.
- Galaxy Server administration
- Computational chemistry
- Contributing to the Galaxy Training Material
- Proteomics
- Variant Analysis
Tutorials
- Microbiome / Pathogen detection from (direct Nanopore) sequencing data using Galaxy - Foodborne Edition 🧐
- Microbiome / 16S Microbial Analysis with mothur (extended) 🧐
- Microbiome / Analyses of metagenomics data - The global picture 🧐
- Microbiome / Antibiotic resistance detection 🧐
- Microbiome / 16S Microbial analysis with Nanopore data 🧐
- Using Galaxy and Managing your Data / Understanding Galaxy history system 📝 🧐
- Using Galaxy and Managing your Data / Downloading and Deleting Data in Galaxy 🧐
- Using Galaxy and Managing your Data / JupyterLab in Galaxy 🧐
- Using Galaxy and Managing your Data / Extracting Workflows from Histories 🧐
- Using Galaxy and Managing your Data / Submitting sequence data to ENA 🧐
- Using Galaxy and Managing your Data / Creating, Editing and Importing Galaxy Workflows 🧐
- Using Galaxy and Managing your Data / SRA Aligned Read Format to Speed Up SARS-CoV-2 data Analysis 🧐
- Using Galaxy and Managing your Data / Name tags for following complex histories 🧐
- Using Galaxy and Managing your Data / RStudio in Galaxy 🧐
- Using Galaxy and Managing your Data / Using dataset collections 🧐
- Using Galaxy and Managing your Data / Group tags for complex experimental designs 🧐
- Using Galaxy and Managing your Data / Rule Based Uploader: Advanced 🧐
- Using Galaxy and Managing your Data / Using Workflow Parameters 🧐
- Galaxy Server administration / Deploying a compute cluster in OpenStack via Terraform 🧐
- Galaxy Server administration / Create a subdomain for your community on UseGalaxy.eu 🧐
- Galaxy Server administration / Galaxy Database schema ✍️
- Galaxy Server administration / Galaxy Installation with Ansible 🧐
- Galaxy Server administration / Galaxy Interactive Tools 🧐
- Galaxy Server administration / Reference Data with CVMFS 🧐
- Galaxy Server administration / Use Apptainer containers for running Galaxy jobs 🧐
- Galaxy Server administration / Data Libraries 🧐
- Galaxy Server administration / Running Jobs on Remote Resources with Pulsar 🧐
- Galaxy Server administration / Ansible 🧐
- Galaxy Server administration / Galaxy Monitoring with gxadmin 🧐
- Galaxy Server administration / External Authentication 🧐
- Galaxy Server administration / Distributed Object Storage 🧐
- Galaxy Server administration / Managing Galaxy on Kubernetes 🧐
- Galaxy Server administration / Mapping Jobs to Destinations using TPV ✍️ 🧐
- Galaxy Server administration / Setting up Celery Workers for Galaxy 🧐
- Galaxy Server administration / Galaxy Monitoring with Telegraf and Grafana 🧐
- Galaxy Server administration / Reference Data with CVMFS without Ansible 🧐
- Galaxy Server administration / Training Infrastructure as a Service (TIaaS) 🧐
- Galaxy Server administration / Automation with Jenkins 🧐
- Galaxy Server administration / Galaxy Tool Management with Ephemeris 🧐
- Galaxy Server administration / Connecting Galaxy to a compute cluster ✍️ 🧐
- Galaxy Server administration / Galaxy Installation on Kubernetes 🧐
- Galaxy Server administration / Upgrading Galaxy 🧐
- Galaxy Server administration / Galaxy Monitoring with Reports ✍️ 🧐
- Visualisation / Genomic Data Visualisation with JBrowse 🧐
- Visualisation / Ploting a Microbial Genome with Circos 🧐
- Visualisation / Visualisation with Circos 🧐
- Single Cell / Importing files from public atlases 🧐
- Single Cell / Filter, plot, and explore single cell RNA-seq data with Seurat 🧐
- Single Cell / Filter, plot and explore single-cell RNA-seq data with Scanpy 🧐
- Single Cell / Combining single cell datasets after pre-processing 🧐
- Single Cell / Analysis of plant scRNA-Seq Data with Scanpy 🧐
- Single Cell / Pre-processing of 10X Single-Cell ATAC-seq Datasets 🧐
- Single Cell / Downstream Single-cell RNA analysis with RaceID 🧐
- Single Cell / Single-cell ATAC-seq standard processing with SnapATAC2 📝 🧐
- Single Cell / Inferring single cell trajectories with Scanpy (Python) 🧐
- Single Cell / Pre-processing of Single-Cell RNA Data 🧐
- Single Cell / Generating a single cell matrix using Alevin 🧐
- Single Cell / Single-cell quality control with scater 🧐
- Single Cell / Bulk RNA Deconvolution with MuSiC 🧐
- Single Cell / Generating a single cell matrix using Alevin and combining datasets (bash + R) 🧐
- Single Cell / Inferring single cell trajectories with Scanpy 🧐
- Single Cell / Clustering 3K PBMCs with Scanpy 🧐
- Single Cell / Pre-processing of 10X Single-Cell RNA Datasets 🧐
- Single Cell / Filter, plot and explore single-cell RNA-seq data with Scanpy (Python) 🧐
- Single Cell / Understanding Barcodes 🧐
- Single Cell / GO Enrichment Analysis on Single-Cell RNA-Seq Data 📝 🧐
- Computational chemistry / Protein-ligand docking 🧐
- Computational chemistry / Virtual screening of the SARS-CoV-2 main protease with rxDock and pose scoring 🧐
- Computational chemistry / Running molecular dynamics simulations using NAMD 🧐
- Computational chemistry / Analysis of molecular dynamics simulations 🧐
- Computational chemistry / Setting up molecular systems 🧐
- Computational chemistry / High Throughput Molecular Dynamics and Analysis ✍️
- Computational chemistry / Running molecular dynamics simulations using GROMACS 🧐
- Teaching and Hosting Galaxy training / Assessment and feedback in training and teachings 🧐
- Teaching and Hosting Galaxy training / Teaching online 🧐
- Teaching and Hosting Galaxy training / Hybrid training 🧐
- Teaching and Hosting Galaxy training / Training Infrastructure as a Service 🧐
- Teaching and Hosting Galaxy training / Set up a Galaxy for Training 🧐
- Teaching and Hosting Galaxy training / Training techniques to enhance learner participation and engagement 🧐
- Teaching and Hosting Galaxy training / Motivation and Demotivation 🧐
- Teaching and Hosting Galaxy training / Organizing a workshop 🧐
- Teaching and Hosting Galaxy training / Galaxy Admin Training 🧐
- Teaching and Hosting Galaxy training / Running a workshop as instructor ✍️ 🧐
- Ecology / QGIS Web Feature Services 🧐
- Ecology / RAD-Seq Reference-based data analysis 🧐
- Ecology / Compute and analyze biodiversity metrics with PAMPA toolsuite 🧐
- Ecology / Obis marine indicators 🧐
- Ecology / RAD-Seq to construct genetic maps 🧐
- Ecology / From NDVI data with OpenEO to time series visualisation with Holoviews 🧐
- Ecology / RAD-Seq de-novo data analysis 🧐
- Ecology / Marine Omics identifying biosynthetic gene clusters 🧐
- Ecology / Regional GAM 🧐
- Ecology / Creating metadata using Ecological Metadata Language (EML) standard with EML Assembly Line functionalities 🧐
- Ecology / Creating FAIR Quality assessment reports and draft of Data Papers from EML metadata with MetaShRIMPS 🧐
- Assembly / De Bruijn Graph Assembly 🧐
- 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 / Chloroplast genome assembly 🧐
- Assembly / Genome Assembly of a bacterial genome (MRSA) sequenced using Illumina MiSeq Data 🧐
- Assembly / Assembly of the mitochondrial genome from PacBio HiFi reads 🧐
- Assembly / Genome Assembly of MRSA from Oxford Nanopore MinION data (and optionally Illumina data) 🧐
- Assembly / Unicycler assembly of SARS-CoV-2 genome with preprocessing to remove human genome reads 🧐
- Assembly / Vertebrate genome assembly using HiFi, Bionano and Hi-C data - Step by Step 🧐
- Assembly / Decontamination of a genome assembly 🧐
- Assembly / An Introduction to Genome Assembly 🧐
- Assembly / ERGA post-assembly QC 🧐
- Assembly / Unicycler Assembly 🧐
- Climate / Getting your hands-on climate data 🧐
- Climate / Ocean's variables study 🧐
- Climate / Visualize Climate data with Panoply netCDF viewer 🧐
- Climate / Ocean Data View (ODV) 🧐
- Climate / Functionally Assembled Terrestrial Ecosystem Simulator (FATES) with Galaxy Climate JupyterLab 🧐
- Climate / Functionally Assembled Terrestrial Ecosystem Simulator (FATES) 🧐
- Climate / Analyse Argo data 🧐
- Sequence analysis / Mapping 🧐
- Sequence analysis / Quality Control 🧐
- Sequence analysis / NCBI BLAST+ against the MAdLand 🧐
- Sequence analysis / Quality and contamination control in bacterial isolate using Illumina MiSeq Data 🧐
- Imaging / Overview of the Galaxy OMERO-suite - Upload images and metadata in OMERO using Galaxy 📝 🧐
- Imaging / Introduction to Image Analysis using Galaxy 🧐
- Imaging / Tracking of mitochondria and capturing mitoflashes 🧐
- Imaging / Nucleoli segmentation and feature extraction using CellProfiler 🧐
- Imaging / Analyse HeLa fluorescence siRNA screen 🧐
- Statistics and machine learning / Deep Learning (Part 3) - Convolutional neural networks (CNN) 🧐
- Statistics and machine learning / Interval-Wise Testing for omics data 🧐
- Statistics and machine learning / Text-mining with the SimText toolset 🧐
- Statistics and machine learning / Age prediction using machine learning 🧐
- Statistics and machine learning / Regression in Machine Learning 🧐
- Statistics and machine learning / Basics of machine learning 🧐
- Statistics and machine learning / Building the LORIS LLR6 PanCancer Model Using PyCaret 🧐
- Statistics and machine learning / Introduction to Machine Learning using R 🧐
- Statistics and machine learning / Clustering in Machine Learning 🧐
- Statistics and machine learning / Fine tune large protein model (ProtTrans) using HuggingFace 🧐
- Statistics and machine learning / Supervised Learning with Hyperdimensional Computing 🧐
- Statistics and machine learning / Machine learning: classification and regression 🧐
- Statistics and machine learning / A Docker-based interactive Jupyterlab powered by GPU for artificial intelligence in Galaxy 🧐
- Statistics and machine learning / Introduction to deep learning 🧐
- Statistics and machine learning / Classification in Machine Learning 🧐
- Evolution / Tree thinking for tuberculosis evolution and epidemiology 🧐
- Evolution / Identifying tuberculosis transmission links: from SNPs to transmission clusters 🧐
- Epigenetics / Infinium Human Methylation BeadChip 🧐
- Epigenetics / Identification of the binding sites of the T-cell acute lymphocytic leukemia protein 1 (TAL1) 🧐
- Epigenetics / ATAC-Seq data analysis 🧐
- Epigenetics / CUT&RUN data analysis 🧐
- Epigenetics / Formation of the Super-Structures on the Inactive X 🧐
- Epigenetics / Identification of the binding sites of the Estrogen receptor 🧐
- Epigenetics / DNA Methylation data analysis 🧐
- Epigenetics / Hi-C analysis of Drosophila melanogaster cells using HiCExplorer 🧐
- Proteomics / Proteogenomics 2: Database Search 🧐
- Proteomics / MaxQuant and MSstats for the analysis of label-free data 🧐
- Proteomics / DIA Analysis using OpenSwathWorkflow 🧐
- Proteomics / Proteogenomics 3: Novel peptide analysis 🧐
- Proteomics / metaQuantome 1: Data creation 🧐
- Proteomics / Detection and quantitation of N-termini (degradomics) via N-TAILS ✍️ 🧐
- Proteomics / Label-free versus Labelled - How to Choose Your Quantitation Method ✍️ 🧐
- Proteomics / Protein FASTA Database Handling ✍️ 🧐
- Proteomics / Clinical Metaproteomics 2: Discovery 🧐
- Proteomics / MaxQuant and MSstats for the analysis of TMT data 🧐
- Proteomics / Clinical Metaproteiomics 1: Database-Generation 🧐
- Proteomics / Library Generation for DIA Analysis 🧐
- Proteomics / Secretome Prediction ✍️ 🧐
- Proteomics / Machine Learning Modeling of Anticancer Peptides 🧐
- Proteomics / Metaproteomics tutorial 🧐
- Proteomics / Peptide and Protein ID using SearchGUI and PeptideShaker ✍️ 🧐
- Proteomics / Proteogenomics 1: Database Creation 🧐
- Proteomics / EncyclopeDIA 🧐
- Proteomics / Peptide and Protein Quantification via Stable Isotope Labelling (SIL) ✍️ 🧐
- Proteomics / Label-free data analysis using MaxQuant 🧐
- Proteomics / Mass spectrometry imaging: Loading and exploring MSI data ✍️ 🧐
- Proteomics / Clinical Metaproteomics 4: Quantitation 🧐
- Proteomics / Clinical Metaproteomics 3: Verification 🧐
- Proteomics / metaQuantome 2: Function 🧐
- Proteomics / Statistical analysis of DIA data 🧐
- Proteomics / Peptide and Protein ID using OpenMS tools ✍️ 🧐
- Proteomics / Clinical Metaproteomics 5: Data Interpretation 🧐
- Proteomics / metaQuantome 3: Taxonomy 🧐
- Proteomics / Peptide Library Data Analysis 🧐
- Proteomics / Annotating a protein list identified by LC-MS/MS experiments 🧐
- FAIR Data, Workflows, and Research / Exporting Workflow Run RO-Crates from Galaxy 🧐
- FAIR Data, Workflows, and Research / Metadata 🧐
- FAIR Data, Workflows, and Research / Data Registration 🧐
- FAIR Data, Workflows, and Research / Access 🧐
- FAIR Data, Workflows, and Research / DataPLANT ARCs 🧐
- FAIR Data, Workflows, and Research / FAIR and its Origins 🧐
- FAIR Data, Workflows, and Research / Persistent Identifiers 🧐
- Contributing to the Galaxy Training Material / Creating Interactive Galaxy Tours ✍️
- Contributing to the Galaxy Training Material / Including a new topic 🧐
- Contributing to the Galaxy Training Material / Teaching Python 🧐
- Contributing to the Galaxy Training Material / GTN Metadata 🧐
- Contributing to the Galaxy Training Material / Tools, Data, and Workflows for tutorials ✍️ 🧐
- Contributing to the Galaxy Training Material / Contributing with GitHub via command-line 🧐
- Contributing to the Galaxy Training Material / Creating content in Markdown 📝 🧐
- Contributing to the Galaxy Training Material / Creating a new tutorial 🧐
- Contributing to the Galaxy Training Material / Running the GTN website locally using the command line ✍️ 🧐
- Contributing to the Galaxy Training Material / Adding Quizzes to your Tutorial 🧐
- Contributing to the Galaxy Training Material / Adding auto-generated video to your slides 🧐
- Contributing to the Galaxy Training Material / Principles of learning and how they apply to training and teaching 🧐
- Contributing to the Galaxy Training Material / Design and plan session, course, materials 🧐
- Contributing to the Galaxy Training Material / FAIR-by-Design methodology 🧐
- Contributing to the Galaxy Training Material / Contributing with GitHub via its interface 🧐
- Contributing to the Galaxy Training Material / Updating diffs in admin training 🧐
- Foundations of Data Science / Introduction to sequencing with Python (part four) 🧐
- Foundations of Data Science / Introduction to sequencing with Python (part three) 🧐
- Foundations of Data Science / Make & Snakemake 🧐
- Foundations of Data Science / SQL Educational Game - Murder Mystery 🧐
- Foundations of Data Science / Introduction to sequencing with Python (part one) 🧐
- Foundations of Data Science / A (very) brief history of genomics 🧐
- Foundations of Data Science / Introduction to sequencing with Python (part two) 🧐
- Foundations of Data Science / Versioning your code and data with git 🧐
- Foundations of Data Science / Data manipulation with Pandas 🧐
- Transcriptomics / Pathway analysis with the MINERVA Platform 🖥 🧐
- Transcriptomics / Genome-wide alternative splicing analysis 🧐
- Transcriptomics / Differential abundance testing of small RNAs 🧐
- Transcriptomics / 3: RNA-seq genes to pathways 🧐
- Transcriptomics / De novo transcriptome reconstruction with RNA-Seq 🧐
- Transcriptomics / Reference-based RNA-Seq data analysis 🧐
- Transcriptomics / De novo transcriptome assembly, annotation, and differential expression analysis 🧐
- Transcriptomics / Visualization of RNA-Seq results with Volcano Plot 🧐
- Transcriptomics / CLIP-Seq data analysis from pre-processing to motif detection 🧐
- Transcriptomics / 1: RNA-Seq reads to counts 🧐
- Transcriptomics / RNA-Seq analysis with AskOmics Interactive Tool 🧐
- Transcriptomics / 2: RNA-seq counts to genes 🧐
- Transcriptomics / Whole transcriptome analysis of Arabidopsis thaliana 🧐
- Transcriptomics / RNA-RNA interactome data analysis 🧐
- Transcriptomics / GO Enrichment Analysis 🧐
- Transcriptomics / Reference-based RNAseq data analysis (long) 🧐
- Transcriptomics / RNA Seq Counts to Viz in R 🧐
- Transcriptomics / Visualization of RNA-Seq results with heatmap2 🧐
- Variant Analysis / Calling very rare variants 🧐
- Variant Analysis / Identification of somatic and germline variants from tumor and normal sample pairs 🧐
- Variant Analysis / Calling variants in non-diploid systems 🧐
- Variant Analysis / Calling variants in diploid systems 🧐
- Variant Analysis / Mapping and molecular identification of phenotype-causing mutations 🧐
- Variant Analysis / Exome sequencing data analysis for diagnosing a genetic disease ✍️ 🧐
- Variant Analysis / Trio Analysis using Synthetic Datasets from RD-Connect GPAP 🧐
- Variant Analysis / From NCBI's Sequence Read Archive (SRA) to Galaxy: SARS-CoV-2 variant analysis 🧐
- Variant Analysis / Mutation calling, viral genome reconstruction and lineage/clade assignment from SARS-CoV-2 sequencing data 🧐
- Variant Analysis / M. tuberculosis Variant Analysis 🧐
- Variant Analysis / Somatic Variant Discovery from WES Data Using Control-FREEC 🧐
- Variant Analysis / Microbial Variant Calling 🧐
- Variant Analysis / Avian influenza viral strain analysis from gene segment sequencing data 🧐
- Genome Annotation / Long non-coding RNAs (lncRNAs) annotation with FEELnc 🧐
- Genome Annotation / Functional annotation of protein sequences 🧐
- Genome Annotation / Refining Genome Annotations with Apollo (prokaryotes) 🧐
- Genome Annotation / Masking repeats with RepeatMasker 🧐
- Genome Annotation / Identification of AMR genes in an assembled bacterial genome 🧐
- Genome Annotation / Genome annotation with Funannotate 🧐
- Genome Annotation / Genome annotation with Maker 🧐
- Genome Annotation / Genome annotation with Helixer 🧐
- Genome Annotation / Genome annotation with Maker (short) 🧐
- Genome Annotation / Genome annotation with Prokka 🧐
- Genome Annotation / CRISPR screen analysis 🧐
- Genome Annotation / Genome Annotation ✍️ 🧐
- Genome Annotation / Bacterial Genome Annotation 🧐
- Genome Annotation / Essential genes detection with Transposon insertion sequencing 🧐
- Genome Annotation / Refining Genome Annotations with Apollo (eukaryotes) 🧐
- Development in Galaxy / Data source integration 🧐
- Development in Galaxy / ToolFactory: Generating Tools From Simple Scripts 🧐
- Development in Galaxy / JavaScript plugins ✍️ 🧐
- Development in Galaxy / Galaxy Interactive Tools 🧐
- Development in Galaxy / Debugging Galaxy 🧐
- Development in Galaxy / Generic plugins 🧐
- Development in Galaxy / Galaxy Webhooks ✍️
- Development in Galaxy / Contributing to BioBlend as a developer 🧐
- Materials Science / Finding the muon stopping site with pymuon-suite in Galaxy 🧐
- Introduction to Galaxy Analyses / Introduction to Genomics and Galaxy 🧐
- Introduction to Galaxy Analyses / A short introduction to Galaxy 🧐
- 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 / Galaxy Basics for genomics ✍️ 🧐
- Introduction to Galaxy Analyses / Galaxy Basics for everyone 🧐
- Introduction to Galaxy Analyses / How to reproduce published Galaxy analyses 🧐
- Galaxy Community Building / Make your tools available on your subdomain 🧐
- Metabolomics / Mass spectrometry imaging: Finding differential analytes 🧐
- Metabolomics / Mass spectrometry: GC-MS data processing (with XCMS, RAMClustR, RIAssigner, and matchms) 🧐
- Metabolomics / Mass spectrometry: LC-MS preprocessing with XCMS 🧐
- Metabolomics / Mass spectrometry imaging: Examining the spatial distribution of analytes 🧐
- Metabolomics / Mass spectrometry: LC-MS analysis 🧐
Slides
- Development in Galaxy / Galaxy from a developer point of view 🧐
- Materials Science / Introduction to Muon Spectroscopy 🧐
- Microbiome / Introduction to metatranscriptomics 🧐
- Microbiome / Introduction to Microbiome Analysis 🧐
- Using Galaxy and Managing your Data / Galaxy workflows in Dockstore 🧐
- Using Galaxy and Managing your Data / Submitting SARS-CoV-2 sequences to ENA 🧐
- Galaxy Server administration / Terraform 🧐
- Galaxy Server administration / uWSGI 🧐
- Galaxy Server administration / Galaxy Monitoring ✍️ 🧐
- Galaxy Server administration / Gearing towards production 🧐
- Galaxy Server administration / Server Maintenance: Cleanup, Backup, and Restoration ✍️ 🧐
- Galaxy Server administration / Galaxy Interactive Tools 🧐
- Galaxy Server administration / Reference Data with CVMFS 🧐
- Galaxy Server administration / Galaxy on the Cloud 🧐
- Galaxy Server administration / Ansible 🧐
- Galaxy Server administration / Reference Genomes in Galaxy 🧐
- Galaxy Server administration / Galaxy Monitoring with gxadmin ✍️ 🧐
- Galaxy Server administration / Empathy 🧐
- Galaxy Server administration / Advanced customisation of a Galaxy instance ✍️ 🧐
- Galaxy Server administration / Storage Management 🧐
- Galaxy Server administration / Galaxy Monitoring with Telegraf and Grafana ✍️ 🧐
- Galaxy Server administration / User, Role, Group, Quota, and Authentication managment ✍️ 🧐
- Galaxy Server administration / Galaxy Tool Management with Ephemeris 🧐
- Galaxy Server administration / Galaxy Troubleshooting 🧐
- Galaxy Server administration / Galaxy from an administrator's point of view ✍️ 🧐
- Galaxy Server administration / Connecting Galaxy to a compute cluster ✍️ 🧐
- Galaxy Server administration / Docker and Galaxy ✍️ 🧐
- Galaxy Server administration / Server: Other ✍️ 🧐
- Visualisation / JBrowse 🧐
- Visualisation / Visualisations in Galaxy 🧐
- Visualisation / Circos 🧐
- Single Cell / Plates, Batches, and Barcodes 🧐
- Single Cell / An introduction to scRNA-seq data analysis 🧐
- Single Cell / Dealing with Cross-Contamination in Fixed Barcode Protocols 🧐
- Single Cell / Clustering 3K PBMCs with Scanpy 🧐
- Single Cell / Automated Cell Annotation 🧐
- Single Cell / Single-cell Formats and Resources 🧐
- Single Cell / GO Enrichment Analysis on Single-Cell RNA-Seq Data 🧐
- Teaching and Hosting Galaxy training / Overview of the Galaxy Training Material for Instructors 🧐
- Assembly / Unicycler assembly of SARS-CoV-2 genome with preprocessing to remove human genome reads 🧐
- Assembly / Unicycler Assembly 🧐
- Climate / Functionally Assembled Terrestrial Ecosystem Simulator (FATES) 🧐
- Sequence analysis / Mapping 🧐
- Sequence analysis / Quality Control 🧐
-
Imaging
/
Nucleoli Segmentation
&
Feature Extraction
using CellProfiler 🧐 - Statistics and machine learning / Convolutional neural networks (CNN) Deep Learning - Part 3 🧐
- Epigenetics / EWAS Epigenome-Wide Association Studies Introduction 🧐
- Epigenetics / Introduction to DNA Methylation data analysis 🧐
- Epigenetics / ChIP-seq data analysis 🧐
- Epigenetics / Introduction to ChIP-Seq data analysis 🧐
- Proteomics / Introduction to proteomics, protein identification, quantification and statistical modelling 🧐
- Contributing to the Galaxy Training Material / Contributing with GitHub via command-line 🧐
- Contributing to the Galaxy Training Material / Creating Slides 🧐
- Contributing to the Galaxy Training Material / Overview of the Galaxy Training Material 🧐
- Transcriptomics / Identification of non-canonical ORFs and their potential biological function 🧐
- Transcriptomics / Introduction to Transcriptomics 🧐
- Variant Analysis / Introduction to Variant analysis 🧐
- Genome Annotation / Genome annotation with Prokka 🧐
- Genome Annotation / Introduction to Genome Annotation 🧐
- Development in Galaxy / Scripting Galaxy using the API and BioBlend 🧐
- Development in Galaxy / Galaxy Interactive Tours ✍️ 🧐
- Development in Galaxy / Tool Shed: sharing Galaxy tools 🧐
- Development in Galaxy / Visualizations: JavaScript Plugins ✍️ 🧐
- Development in Galaxy / Generic plugins 🧐
- Development in Galaxy / Tool Dependencies and Containers ✍️ 🧐
- Development in Galaxy / Tool Dependencies and Conda ✍️ 🧐
- Development in Galaxy / Galaxy Interactive Environments ✍️ 🧐
- Development in Galaxy / Tool development and integration into Galaxy ✍️ 🧐
- Development in Galaxy / Galaxy Webhooks ✍️ 🧐
- Development in Galaxy / Prerequisites for building software/conda packages 🧐
- Development in Galaxy / Galaxy Code Architecture ✍️ 🧐
- Introduction to Galaxy Analyses / A Short Introduction to Galaxy 🧐
- Introduction to Galaxy Analyses / Options for using Galaxy 🧐
- Introduction to Galaxy Analyses / Introduction to Galaxy 🧐
- Metabolomics / Mass spectrometry: LC-MS preprocessing - advanced 🧐
- Single Cell / Introducción al análisis de datos de scRNA-seq 🧐
- Single Cell / Una introducción al análisis de datos scRNA-seq 🧐
FAQs
Events
GitHub Activity
github Issues Reported
62 Merged Pull Requests
See all of the github Pull Requests and github Commits by Björn Grüning.
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tiny edits to LOTUS2
microbiome
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adds the missing workflow-hub icon
template-and-tools
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Add ELIXIR and a few other affiliations
template-and-tools
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fix build
proteomics
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adding uni-freiburg affi
template-and-tools
Reviewed 931 PRs
We love our community reviewing each other's work!
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Put in correct zone
single-cell
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Add end-of-year blog post for SPOC Community
news
- Add one line
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Add scrna-plant WF tests
single-cell
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PyCaret - LORIS Tutorial
statistics
News
4th Mycobacterium tuberculosis complex NGS made easy
8 July 2024
Tuberculosis (TB) is a big killer in many countries of the world, particularly in those with low and middle income. Next-generation sequencing has been key in improving our understanding of drug resistance acquisition and of transmission of Mycobacterium tuberculosis. Yet, the need for expertise guiding NGS implementation in laboratories and the lack of bioinformatic expertise, are main obstacles hindering the implementation of NGS into TB programs.
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