Plant lovers are in luck! A new tutorial on this fascinating kingdom has been added to the GTN. It details the necessary steps to identify potential targets of brassinosteroid-induced miRNAs. Brassinosteroids are phytohormones that have the ability to stimulate plant growth and confer resistance against abiotic and biotic stresses. These characteristics have led to great interest in the field of biotechnology due to its potential for increasing agricultural productivity.
Full StoryCristóbal Gallardo
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.
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.
Tutorials
- Microbiome / Pathogen detection from (direct Nanopore) sequencing data using Galaxy - Foodborne Edition 🧐
- Microbiome / Taxonomic Profiling and Visualization of Metagenomic Data 🧐
- Microbiome / 16S Microbial analysis with Nanopore data ✍️ 🧐
- Microbiome / Identification of the micro-organisms in a beer using Nanopore sequencing 🧐
- Using Galaxy and Managing your Data / Understanding Galaxy history system 📝
- Using Galaxy and Managing your Data / Rule Based Uploader 🧐
- Using Galaxy and Managing your Data / Group tags for complex experimental designs 🧐
- Visualisation / Visualisation with Circos ✍️ 🧐
- Single Cell / Analysis of plant scRNA-Seq Data with Scanpy ✍️
- Single Cell / Pre-processing of 10X Single-Cell ATAC-seq Datasets 🧐
- Single Cell / Pre-processing of 10X Single-Cell RNA Datasets 🧐
- Teaching and Hosting Galaxy training / Assessment and feedback in training and teachings 🧐
- Teaching and Hosting Galaxy training / Train-the-Trainer: putting it all together 🧐
- Teaching and Hosting Galaxy training / Training techniques to enhance learner participation and engagement 🧐
- Teaching and Hosting Galaxy training / Motivation and Demotivation 🧐
- Synthetic Biology / Generating theoretical possible pathways for the production of Lycopene in E.Coli using Retrosynthesis tools 🧐
- Ecology / Metabarcoding/eDNA through Obitools 🧐
- Assembly / Genome assembly using PacBio data 🧐
- 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 / Genome Assembly Quality Control 🧐
- Assembly / Large genome assembly and polishing 🧐
- 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 / An Introduction to Genome Assembly 🧐
- Assembly / ERGA post-assembly QC ✍️ 🧐
- Climate / Pangeo ecosystem 101 for everyone - Introduction to Xarray Galaxy Tools 🧐
- Climate / Pangeo Notebook in Galaxy - Introduction to Xarray 🧐
- Sequence analysis / Quality Control 🧐
- Sequence analysis / NCBI BLAST+ against the MAdLand 🧐
- Imaging / Object tracking using CellProfiler 🧐
- Epigenetics / Formation of the Super-Structures on the Inactive X 🧐
- Contributing to the Galaxy Training Material / Creating content in Markdown 🧐
- 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 🧐
- Foundations of Data Science / Advanced R in Galaxy 🧐
- Transcriptomics / Genome-wide alternative splicing analysis ✍️ 🧐
- Transcriptomics / Reference-based RNA-Seq data analysis 🧐
- Transcriptomics / Whole transcriptome analysis of Arabidopsis thaliana ✍️ 🧐
- Transcriptomics / Network analysis with Heinz 🧐
- Variant Analysis / M. tuberculosis Variant Analysis 🧐
- Genome Annotation / Masking repeats with RepeatMasker 🧐
- Genome Annotation / From small to large-scale genome comparison 🧐
- Genome Annotation / Genome annotation with Funannotate 🧐
- Development in Galaxy / Contributing to BioBlend as a developer 🧐
- Introduction to Galaxy Analyses / Introduction to Genomics and Galaxy ✍️ 🧐
- Introduction to Galaxy Analyses / A short introduction to Galaxy 🧐
- Introduction to Galaxy Analyses / Galaxy Basics for genomics 🧐
- Metabolomics / Mass spectrometry : GC-MS analysis with metaMS package 🧐
- Single Cell / Filtrado, representación y exploración de secuenciación de ARN de células únicas 🧐
- Introduction to Galaxy Analyses / Breve introducción a Galaxy - en español 🧐
Slides
- Development in Galaxy / Galaxy from a developer point of view 🧐
- Microbiome / Introduction to metatranscriptomics 🧐
- Microbiome / Introduction to Microbiome Analysis 🧐
- Using Galaxy and Managing your Data / Getting data into Galaxy 🧐
- Galaxy Server administration / Terraform 🧐
- Galaxy Server administration / Galaxy on the Cloud 🧐
- Galaxy Server administration / Galaxy from an administrator's point of view 🧐
- Galaxy Server administration / Docker and Galaxy 🧐
- Visualisation / Visualisations in Galaxy 🧐
- Single Cell / An introduction to scRNA-seq data analysis 🧐
- Teaching and Hosting Galaxy training / Workshop Kickoff 🧐
- Assembly / De Bruijn Graph Assembly 🧐
- Assembly / An introduction to get started in genome assembly and annotation 🧐
- Assembly / Genome assembly quality control. 🧐
- Assembly / Unicycler assembly of SARS-CoV-2 genome with preprocessing to remove human genome reads ✍️ 🧐
- Assembly / An Introduction to Genome Assembly 🧐
- Assembly / Unicycler Assembly 🧐
- Climate / Pangeo ecosystem 101 for everyone 🧐
- Climate / The Pangeo ecosystem 🧐
- 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 🧐
- Statistics and machine learning / Feedforward neural networks (FNN) Deep Learning - Part 1 🧐
- Epigenetics / EWAS Epigenome-Wide Association Studies Introduction 🧐
- Epigenetics / Introduction to DNA Methylation data analysis 🧐
- Epigenetics / Introduction to ATAC-Seq 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 🧐
- Transcriptomics / Identification of non-canonical ORFs and their potential biological function ✍️ 🧐
- Transcriptomics / Integrate and query local datasets and distant RDF data with AskOmics using Semantic Web technologies 🧐
- Transcriptomics / Whole transcriptome analysis of Arabidopsis thaliana ✍️ 🧐
- Transcriptomics / Network Analysis with Heinz 🧐
- Transcriptomics / Introduction to Transcriptomics 🧐
- Variant Analysis / Introduction to Variant analysis 🧐
- Genome Annotation / High Performance Computing for Pairwise Genome Comparison 🧐
- Genome Annotation / Introduction to Genome Annotation 🧐
- 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 / 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 🧐
- Metabolomics / Introduction to Metabolomics 🧐
- Introduction to Galaxy Analyses / Una Breve Introducción a Galaxy 🧐
FAQs
- Could I use a different p-adj value for filtering differentially expressed genes?
- Can I use alternative tools for the Quantification step?
- Import workflows from WorkflowHub
Video Recordings
- Transcriptomics / Whole transcriptome analysis of Arabidopsis thaliana 💬
- Galaxy Server administration / Use Apptainer containers for running Galaxy jobs 💬
- Assembly / Unicycler assembly of SARS-CoV-2 genome with preprocessing to remove human genome reads 🗣
- Transcriptomics / Whole transcriptome analysis of Arabidopsis thaliana 💬 🗣
- Development in Galaxy / Creating Galaxy tools from Conda Through Deployment 💬 🗣
GitHub Activity
github Issues Reported
65 Merged Pull Requests
See all of the github Pull Requests and github Commits by Cristóbal Gallardo.
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Genome-wide alternative splicing: add slides and fix typos
transcriptomics
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Learning principles training: fix references
contributing
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Genome-wide alternative splicing training v.2.0
review-neededtranscriptomics
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Add as contributor to Learning principles training
contributing
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Alternative splicing training: improve introduction
transcriptomics
Reviewed 74 PRs
We love our community reviewing each other's work!
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Small updates from feedback from the last workshop
metagenomics
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Update ChIP-Seq tutorial with latest tool versions and links
epigenetics
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Genome-wide alternative splicing: add slides and fix typos
transcriptomics
- github Auto Compress Images
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ERGA post-assembly QC training
template-and-toolsassembly
News
We are proud to announce that, as result of the collaboration with the Vertebrate Genomes Project (VGP), a new training describing the VGP assembly pipeline is now available in the Galaxy Training Network. The Vertebrate Genomes Project aims to generate high-quality, near-error-free, gap-free, chromosome-level, haplotype-phased, annotated reference genome assemblies for every vertebrate species.
Full StoryAuthor(s) | Cristóbal Gallardo |
The GTN hosts a new training for analyzing alternative splicing at genome-wide scale!
Full Story