Glasgow Bioinformatics Summer School 2019
When: 26/08/2019 - 30/08/2019. (Confirmed)
Application Deadline: 15/07/2019
Topics: (see below for more details):
- Basics of Linux
- Introduction to R
- Introduction to next generation sequencing
- Data visualization
- SNP analysis
- Transcriptomics: bulk RNA-Seq and single cell RNA-Seq
- Sequence Assembly and Annotation (incl. Companion) with (parallel session to single cell RNA-Seq and ChipSeq)
- Data processing
Keynote speaker: We are happy to welcome John Maroni as keynote speaker! (28/08/2019)
Cost: £600 for academics / £1000 commercial
How to apply: Places are assigned on a first come to first served basis upon receipt of the fee. Please contact email@example.com for the booking.
Cancellation policy: >= 30 days before the start date = 30% cancellation fee; <30 days before the start date= No Refund.
Participants are encouraged to attend the full course, daily, core hours 9:00-19:00h.
Next generation sequencing (NGS) and bioinformatics has become an essential tool in genetic and genomic analysis. It is increasingly important for experimental scientists to gain the bioinformatics skills required to assess and analyse the large volumes of sequencing data produced by next generation sequencers. With the ongoing omics initiatives, we would like to give PhD students and postdocs the opportunity to learn about NGS and bioinformatics.
This week-long course aims to provide experimental biologists working with omics data with (i) a comprehension of “bioinformatics” language and terminology, (ii) an understanding of the underlying concepts (iii) hands-on experience in genomic-scale data analysis for
- Linux: The operating system for most bioinformatics software. This part will also explain how to process data on the Glasgow high performance compute cluster (HPCC each participant will need an account, information to follow). This will allow participants to apply the knowledge they have gained in the future.
- NGS mapping and variant calling: Learn how to map sequencing reads and visualize the data. Find copy number and sequence variants and understand the different types of variation.
- Analyse a dataset by comparing the transcriptome of a knock-out versus a wildtype parasite - from the mapping of short reads, visualization, differential expression up to GO enrichment!
- Single cell RNA-Seq
- R is a statistical package based on a Linux like syntax. Many tools for genomics and transcriptomics analysis are written in R. We will explore using some of these tools and creating publication-ready figures in R
- Chip-Seq: Analysis of genome-wide DNA-protein interactions
The data used during the workshop will be derived from bacteria, single celled parasites and human or mouse, but the learning outcomes can be applied to other organisms.
At the end of the course you will have the opportunity to work on a larger task with a group to gain experience of applying the learning outcomes of the course independently. If you wish to bring your own data for the group task, please contact the course organisers in advance.
Initially, participants will work from a virtual machine, which will be provided on a USB hard disc, and can be taken away at the end of the course at no additional cost. Some exercises will be taught on the Glasgow high performance compute cluster.
After attending this course, participants should be able to:
- Comfortably work with state-of-the-art bioinformatics software in a Linux-like environment
- Have a good understanding of the application, opportunities, visualization and analysis of next generation sequencing datasets
- Integrate and query large-scale genomic and functional genomic databases to answer biology-related research questions and develop testable hypotheses
- Experience analysing RNA-Seq and ChIP-seq data for measuring abundance
- Ideas around integrative analysis and how to run basic analysis in R
Please note: The practical sessions will be taught exclusively through Unix/Linux. Knowledge in Linux is helpful, but not required. The course aims to provide a hands-on introduction to bioinformatics for next generation sequencing and should not be considered a complete education in the theoretical and mathematical foundations of the topics. This course is aimed at applicants solely interested in analysis of NGS data and bioinformatics.
About the organisers
Thomas Otto is a Senior lecturer for Bioinformatics at the University of Glasgow. He has a vast experience in NGS genomics, from the basics of sequencing technologies, quality control of data, genome and transcriptomic projects and genotype to phenotype projects.
Through his career, he taught many workshops on NGS genomics, including de novo assembly, Introduction to bioinformatics (Wellcome Trust advanced courses (WTAC)), more applied workshops like working with pathogen genomes or working with parasite databases. He is also teaching masters courses like single-cell sequencing at the University of Glasgow.
Kathryn Crouch is team leader for the bioinformatics team at the Wellcome Centre for Molecular Parasitology, University of Glasgow. Her background is in comparative immunology and she worked in the pharmaceutical industry for several years before taking up her current position.
In her current role, she manages a team providing advice and computational analysis to Wellcome Centre members working with NGS and other high throughput data in eukaryotic pathogens. She also develops software for the EuPathDB suite of databases (www.eupathdb.org). Teaching experience includes running an applied bioinformatics module on the MSc Bioinformatics at the University of Glasgow for the last three years, and contributing to applied courses including the Wellcome Trust Advanced Courses Working with Parasite Database Resources workshop for the last four years.