This page shows you only the multi-video “sessions” of available GTN video tutorials, you might also be interested in the full video library which includes every single video known to the GTN Video Library.
All Training Sessions
Sessions are multi-video trainings often taught as a unit, for example a lecture video and a hands-on video from the same GTN tutorial.
Webinar
In this webinar series, we cover resources for different types of Galaxy users and audiences.
Galaxy Resources for.. Researchers (Webinar)
Description:
Wondering how to get started, or how to do a particular type of analysis, or how to scale to thousands of datasets? This webinar will highlight how to find the resources and help you need for each of these questions and more.
Variation in the genome of M. tuberculosis (Mtb) is associated with changes in phenotype, for example drug resistance and virulence. It is also useful for outbreak investigation as the single nucleotide polymorphisms (SNPs) in a sample can be used to build a phylogeny.
M. tuberculosis Variant Analysis (Lecture)
Description:
Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium tuberculosis. According to the WHO, in 2018 there were 10.0 million new cases of TB worldwide and 1.4 million deaths due to the disease, making TB the world’s most deadly infectious disease.
Variation in the genome of M. tuberculosis (Mtb) is associated with changes in phenotype, for example drug resistance and virulence. It is also useful for outbreak investigation as the single nucleotide polymorphisms (SNPs) in a sample can be used to build a phylogeny.
In this sesssion, we will walk you through the basics of quality checking your sequencing data. This session consists of a lecture followed by a hands-on tutorial.
Quality Control (Lecture)
Description:
This lecture goes over the concepts involved in assessing the quality of your sequencing data.
In this sesssion, we will walk you through the basics of mapping your sequencing data to a reference genome. This session consists of a lecture followed by a hands-on tutorial.
Mapping (Lecture)
Description:
This lecture covers the basic concepts involved in mapping sequencing reads to a reference genome.
Variation in the genome of M. tuberculosis (Mtb) is associated with changes in phenotype, for example drug resistance and virulence. It is also useful for outbreak investigation as the single nucleotide polymorphisms (SNPs) in a sample can be used to build a phylogeny.
M. tuberculosis Variant Analysis (Lecture)
Description:
Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium tuberculosis. According to the WHO, in 2018 there were 10.0 million new cases of TB worldwide and 1.4 million deaths due to the disease, making TB the world’s most deadly infectious disease.
Variation in the genome of M. tuberculosis (Mtb) is associated with changes in phenotype, for example drug resistance and virulence. It is also useful for outbreak investigation as the single nucleotide polymorphisms (SNPs) in a sample can be used to build a phylogeny.
ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) is a technique used in molecular biology to assess genome-wide chromatin accessibility. This session will introduce ATAC-Seq and walk you through an analysis step by step.
ATAC-Seq data analysis (Lecture)
Description:
This lecture will introduce the basic concepts involved in ATAC-Seq analysis.
Single-cell RNA-seq analysis is a rapidly evolving field at the forefront
of transcriptomic research, used in high-throughput developmental studies
An introduction to scRNA-seq data analysis (Lecture)
Description:
Single-cell RNA-seq analysis is a rapidly evolving field at the forefront of transcriptomic research, used in high-throughput developmental studies and rare transcript studies to examine cell heterogeneity within a populations of cells. The cellular resolution and genome wide scope make it possible to draw new conclusions that are not otherwise possible with bulk RNA-seq. Slides created by Mehmet Tekman.
Filter, plot and explore single-cell RNA-seq data (Scanpy) (Demo)
Description:
You’ve done all the work to make a single cell matrix, with gene counts and mitochondrial counts and buckets of cell metadata from all your variables of interest, now it’s time to fully process our data, to remove low quality cells, to reduce the many dimensions of data that make it difficult to work with, and ultimately to try to define our clusters and to find our biological meaning and insights!
Interpret quality control plots to direct parameter decisions
Repeat analysis from matrix to clustering
Identify decision-making points
Appraise data outputs and decisions
Explain why single cell analysis is an iterative (i.e. the first plots you generate are not final, but rather you go back and re-analyse your data repeatedly) process
In plants, miRNAs can silence targets through RNA degradation as well as translational repression pathways, and unlike animals, a large proportion of miRNA and their targets have less than four mismatches. This feature has been exploited for developing miRNAs target prediction tools, providing an efficient approach to elucidate the miRNA-mediated regulatory networks, which can contribute to biotechnological solutions to improve crops productivity.
Whole transcriptome analysis of Arabidopsis thaliana (Lecture)
Description:
In plants, miRNAs can silence targets through RNA degradation as well as translational repression pathways, and unlike animals, a large proportion of miRNA and their targets have less than four mismatches. This feature has been exploited for developing miRNAs target prediction tools, providing an efficient approach to elucidate the miRNA-mediated regulatory networks, which can contribute to biotechnological solutions to improve crops productivity.
Whole transcriptome analysis of Arabidopsis thaliana (Tutorial)
Description:
In plants, miRNAs can silence targets through RNA degradation as well as translational repression pathways, and unlike animals, a large proportion of miRNA and their targets have less than four mismatches. This feature has been exploited for developing miRNAs target prediction tools, providing an efficient approach to elucidate the miRNA-mediated regulatory networks, which can contribute to biotechnological solutions to improve crops productivity.
Single-cell RNA-seq analysis is a rapidly evolving field at the forefront
of transcriptomic research, used in high-throughput developmental studies
An introduction to scRNA-seq data analysis (Lecture)
Description:
Single-cell RNA-seq analysis is a rapidly evolving field at the forefront of transcriptomic research, used in high-throughput developmental studies and rare transcript studies to examine cell heterogeneity within a populations of cells. The cellular resolution and genome wide scope make it possible to draw new conclusions that are not otherwise possible with bulk RNA-seq. Slides created by Mehmet Tekman.
Filter, plot and explore single-cell RNA-seq data (Scanpy) (Demo)
Description:
You’ve done all the work to make a single cell matrix, with gene counts and mitochondrial counts and buckets of cell metadata from all your variables of interest, now it’s time to fully process our data, to remove low quality cells, to reduce the many dimensions of data that make it difficult to work with, and ultimately to try to define our clusters and to find our biological meaning and insights!
Interpret quality control plots to direct parameter decisions
Repeat analysis from matrix to clustering
Identify decision-making points
Appraise data outputs and decisions
Explain why single cell analysis is an iterative (i.e. the first plots you generate are not final, but rather you go back and re-analyse your data repeatedly) process
This tutorial will introduce genome annotation process and give you hands-on experience with annotating a prokaryotic genome using Prokka.
Genome annotation with Prokka (Lecture)
Description:
Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.
In this tutorial we will use Prokka to annotate a draft genome sequence. Prokka finds and annotates features (both protein coding regions and RNA genes, i.e. tRNA, rRNA) present on on a sequence. Prokka can be used to annotate bacterial, archaeal and viral genomes quickly, generating standard output files in GenBank, EMBL and gff formats.”
Data independent acquisition (DIA) mass spectrometry is a powerful technique that is improving the
reproducibility and throughput of proteomics studies. EncyclopeDIA is library search engine comprised of
several algorithms for DIA data analysis and can search for peptides using either DDA-based spectrum libraries
or DIA-based chromatogram libraries.
Proteogenomics is a field of biological research that utilizes a combination of proteomics, genomics, and
transcriptomics to aid in the discovery and identification of peptides
Proteogenomics 1: Database Creation (Tutorial)
Description:
In this tutorial, we will provide a walkthrough on how to generate a customized protein sequence database using RNA-Seq data. The resultant FASTA database contains sequences with single amino acid variants (SAVs), insertions and deletions (indels)and transcript assemblies (splicing variants). This database can then be used to identify protein sequence variants from the mass spectrometry data.
In this demonstration, we’re continuing the process of proteogenomic analysis. Here, we search mass spectrometry data against a custom proteogenomics FASTA database to create peptide spectral matches (PSMs) for each dataset; we also isolate non-canonical peptides from the resulting data for further analysis. If you would like to view the results yourself, we provide example histories in the FAQ document
In this demonstration, we will investigate the peptides that were identified during proteogenomics tutorial 2. We will identify the presence of novel proteoforms that are absent in the reference database, annotate the novel peptides and visualize them using the Multi-omics Visualization Platform (MVP). If you would like to view the results yourself, we provide example histories in the FAQ document
To determine the composition of a microbiome sample, sequencing of the 16S rRNA gene
is often used. This allows us to identify the bacterial species present in our sample.
This lecture and practical session introduces you to 16S analysis in Galaxy using the
mothur tool suite.
Introduction to Microbiome Analysis (Lecture)
Description:
This lecture briefly introduces 16S sequencing, a popular technique used for taxonomic profiling of microbial communities.
In this 3-part module, you will learn about Nanopore long-read sequencing for the
detection of antimicrobial resistance (AMR). There is a short video showing you the
wetlab steps involved in using the MinION sequencer. A talk about the clinical applications,
and finally a practical tutorial walking you through an AMR analysis in Galaxy.
MinION Wetlab demo (Demo)
Description:
This video will show you the full process of sequencing a bacterial genome using the Oxford Nanopore MinION sequencer.
Nanopore Whole Bacterial Genome Sequencing in a Clinical Setting (Lecture)
Description:
Nanopore Sequencing has many applications in a clinical setting. In this lecture, Astrid Heikema discusses how her group at the Erasmus Medical Center uses Nanopore for sequencing of bacterial Genomes.
This tutorial will guide you through the process of assembling your Nanopore-sequenced bacterial samples and determining the presence of antibiotic resistance genes.
In this 3-part module, you will learn about Nanopore long-read sequencing for the
detection of antimicrobial resistance (AMR). There is a short video showing you the
wetlab steps involved in using the MinION sequencer. A talk about the clinical applications,
and finally a practical tutorial walking you through an AMR analysis in Galaxy.
MinION Wetlab demo (Demo)
Description:
This video will show you the full process of sequencing a bacterial genome using the Oxford Nanopore MinION sequencer.
Nanopore Whole Bacterial Genome Sequencing in a Clinical Setting (Lecture)
Description:
Nanopore Sequencing has many applications in a clinical setting. In this lecture, Astrid Heikema discusses how her group at the Erasmus Medical Center uses Nanopore for sequencing of bacterial Genomes.
This tutorial will guide you through the process of assembling your Nanopore-sequenced bacterial samples and determining the presence of antibiotic resistance genes.
This 3-part session will introduce you to the world of deep learning and cover Feedforward
Neural Networks (FNN), Recurrent Neural Networks (FNN), and Convolutional Neural Networks
(CNN).
Feedforward Neural Networks (FNN) (Tutorial)
Description:
This hands-on tutorial covers Feedforward Neural Networks (FNN)
This session will introduce the SRA Aligned Read format, and show you how to use this in Galaxy to analyze a SARS-CoV-2 dataset.
SRA Aligned Read Format to Speed Up SARS-CoV-2 data Analysis (Lecture)
Description:
This lecture will introduce the SRA Aligned Read format available in the cloud from SRA, as well as some accompanying metadata that can help you search and filter the data. This sessions is aimed specifically at SARS-CoV-2 runs in SRA.
Want a bit more control over your Analyses? You can run R in Rstudio directly within Galaxy
Running RStudio on Galaxy (Demo)
Description:
This tutorial will show you how you can start Rstudio from within Galaxy. This option is only available on Galaxy EU for the time being. If you are working on a different Galaxy server, you can use Rstudio Cloud (https://rstudio.cloud/)
Want a bit more control over your Analyses? You can run R in Rstudio directly within Galaxy
Running RStudio on Galaxy (Demo)
Description:
This tutorial will show you how you can start Rstudio from within Galaxy. This option is only available on Galaxy EU for the time being. If you are working on a different Galaxy server, you can use Rstudio Cloud (https://rstudio.cloud/)
Circos (Krzywinski et al. 2009) is a software package for visualizing data in a circular layout. This makes Circos ideal for exploring relationships between objects or positions. Circos plots have appeared in thousands of scientific publications. Although originally designed for visualizing genomic data, it can create figures from data in any field.
Visualisation with Circos (Lecture)
Description:
Circos is a popular tool for creating circular graphs to display genomic data. This video will introduce this tool and how to use it within Galaxy