In this module, we will introduce the most used sequencing technologies and explain their concepts. Using different datasets, we will practice quality control, alignment of reads to a reference genome and visualize the output. This course is intended for life scientists who are already dealing with NGS data and would like to be able to start analysing them.
This 3-day Nextflow course by ELIXIR Estonia, in collaboration with the University of Tartu HPC Center, comprehensively introduces the powerful workflow language. Nextflow is renowned for its robust, scalable, and reproducible methods of running computational pipelines. Through efficient, interactive lessons, participants will gain a solid understanding of Nextflow technology, from fundamental to advanced concepts.
Experiments designed to quantify gene expression often yield hundreds of genes that show statistically significant differences between groups of interest. Once differentially expressed genes are identified, enrichment analysis (EA) methods can be used to explore the biological functions associated with these genes. EA methods allow us to identify groups of genes (e.g. particular pathways) that are over-represented, thereby offering insights into biological mechanisms. One of the EA methods frequently used for high-throughput gene expression data analysis is Gene Set Enrichment Analysis (GSEA). This course will cover GSEA and alternative enrichment methods. Because the implementation of GSEA is directly linked to databases that annotate the function of genes in a cell, the course will also give an overview of functional annotation databases such as Gene Ontology.
The detection of genetic variation is of major interest in various disciplines spanning from ecology and evolution research to inherited disease discovery and precision oncology. Next generation sequencing (NGS) methods are very powerful for the detection of genomic variants. Thanks to its throughput and cost-efficiency it enables the detection of a large number of variants in a large number of samples. In this two-day course we will cover the steps from read alignment to variant calling and annotation. We will mainly focus on the detection of germline mutations by following the GATK best practices.
The 9th edition of the RNA-seq Data Analysis course will be held on 8-12 April – 2024 in Breda, The Netherlands. This course covers the basic concepts and methods required for RNA-seq analysis. Particular attention is given to the data analysis pipelines for differential transcript expression and variant calling. The course consists of a mixture of lectures and Galaxy, Linux and R practicals. Also the potential of long-read based RNA-seq and AI based analysis enrichments will be explored.
Single-cell RNA sequencing (scRNAseq) allows researchers to study gene expression at the single cell level. For example, scRNAseq can help to identify expression patterns that differ between conditions within a cell-type. To generate and analyze scRNAseq data, several methods are available, all with their strengths and weaknesses depending on the researchers’ needs. This 3-day course will cover the main technologies as well as the main aspects to consider while designing a scRNAseq experiment. In addition, it will cover the theoretical background of analysis methods with hands-on practical data analysis sessions applied to droplet-based methods.
European Bioinformatics Institute United Kingdom in association with Elixir Estonia are organising summer school in bioinformatics. This course provides an introduction to the use of bioinformatics in biological research, giving you guidance for using bioinformatics in your work whilst also providing hands-on training in tools and resources appropriate to your research.
Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their knowledge and skills further. No previous knowledge of programming is required for this course.
European Bioinformatics Institute United Kingdom in association with Elixir Estonia are organising summer school in bioinformatics. This course provides an introduction to the use of bioinformatics in biological research, giving participants guidance for using bioinformatics in their work whilst also providing hands-on training in tools and resources appropriate to their research.
Participants will initially be introduced to bioinformatics theory and practice, including best practices for undertaking bioinformatics analysis, data management, and reproducibility. To enable specific exploration of resources in their particular field of interest, participants will then be divided into focused groups to work on a project.
Participants will be required to review some pre-recorded material prior to the start of the course.
Information about the summer school
Date: 12 - 16 June 2023
Application deadline: 05 March 2023
Cost: £825.00 inclusive of four nights accommodation and catering, including dinner
Participant limit: Open application with selection 30 places
Interpreting functional information from large scale protein structure data
Modelling cell signalling pathways
Networks and pathways
Reusing FAIR Bioimage data: an AI application
Who is this course for?
Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their knowledge and skills further. No previous knowledge of programming is required for this course; group projects may give you the opportunity to learn basic programming, but participants will be supported in this by their mentors. Depending on your chosen project, an introductory programming tutorial may be given as homework prior to attending the course.
After this course you should be able to:
Discuss applications of bioinformatics in biological research
Browse, search, and retrieve biological data from public repositories
Use appropriate bioinformatics tools to explore biological data
Describe ways that biological data can be stored, organised and integrated
Bioinformaticians of the world, it's your time to shine! The SIB Bioinformatics Awards promote excellence, diversity and innovation in the field of bioinformatics, and are now open to entries until 31 January 2023.
SIB created the Bioinformatics Awards in 2008 to acknowledge early career bioinformaticians and ground-breaking resources of national and international standing. The international awards honour excellence in bioinformatics and computational biology within three categories:
Unix Shell Advanced Courses 17th and 20th of March 2020, 10.15-14.00, Delta #2005
Advanced computing power is hidden away in clouds/cluster/supercomputers that you do not have click and point access. As a general rule these high performance computer resources use Linux operating systems and are accessible only by a shell terminal.
This course is aimed to streamline your skills in Linux and terminal environment. We will teach you how to make your life easier by creating maintainable and flexible bash scripts for your commonly used workflows or SLURM jobs.
Learn how to iterate operations over many input files with bash loops and conditions.
Learn how to combine complicated command line based workflows into maintainable bash scripts.
Add additional useful utility functions and tools to your toolbox.
Expected prior knowledge:
Experience in using the basic commands covered in the Basics course (e.g. cd, ls, mkdir, mv, cp, head, cat, find, less, pwd).
Lecture venue is computer class with linux computers. In case you bring your own Windows laptop, please make sure to install Putty application (https://www.putty.org/) beforehand.