A week long ecology course at the Refugio  de Binifaldo, Majorca.

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18-22 July 2022

 Python is a dynamic, readable language that is a popular platform for all types of bioinformatics work, from simple one-off scripts to large, complex software projects. This workshop is aimed at complete beginners. It gives an overview of the language with an emphasis on practical problem-solving, using examples and exercises drawn from various aspects of bioinformatics work. The workshop is structured so that the parts of the language most useful for bioinformatics are introduced as early as possible, and that students can start writing plausibly-useful programs after the first few sessions. After completing the workshop, students should be in a position to (1) apply the skills they have learned to tackling problems in their own research and (2) continue their Python education in a self-directed way.

Workshop format

The workshop is delivered over five taught days, running 9am - 5pm with a break for lunch at 12:30. 

Who should attend

This workshop is aimed at researchers and technical workers with a background in biology who want to learn programming. The syllabus has been planned with complete beginners in mind; people with previous programming experience are welcome to attend as a refresher but may find the pace a bit slow.

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The aim of this course is to introduce participants to the statistical computing language 'R' using examples and skills relevant to biological data science. This online workshop is taught by experienced Edinburgh Genomics’ trainers. By the end of the workshop, you will be comfortable with the basics of the R and R studio environments, learning about the rules of the language and how R works with different data types and structures. We then move on to using functions, introducing a selection of packages for biological data science. Finally, we will learn how to visualise your data to generate publication-ready plots using the package ggplot2.

Instructors

• Nathan Medd (Training and Outreach Manager)
• Frances Turner (Bioinformatician) 

Workshop format

The workshop consists of presentations and hands-on tutorials.

Who should attend

Undergraduates, Graduates, postgraduates, and PIs, who are using, or planning to use, the statistical software R to manipulate and analyse biological data in their research. This is an introductory level course: no prior experience of R (or any other programming language) is necessary before starting the workshop.

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Edinburgh Genomics: RNA-seq Data Analysis

RNA sequencing (RNA-seq) has become the method of choice for transcriptome profiling. Nevertheless, it is a non-trivial task to transform the vast amount of data obtained with high-throughput sequencers into useful information. Thus, RNA-seq data analysis is still a major bottleneck for most researchers in this field. The ability to correctly interpret RNA-seq results, as well as knowledge of the intrinsic properties of these data, are essential to avoid incorrect experimental designs and the application of inappropriate analysis methodologies. The aim of this workshop is to familiarise researchers with RNA-seq data and to initiate them in the analysis by providing lectures and practicals on analysis methodologies. In the practicals Illumina-generated sequencing data and various widely used software programs will be used.

Instructors: Urmi Trivedi, Frances Turner, Nathan Medd 

Workshop format

The workshop consists of presentations and hands-on tutorials.

Who should attend

Graduates, postgraduates, and PIs, who are using, or planning to use, RNA-seq technology in their research and want to learn how to process and analyse RNA-seq data.

Requirements

A general understanding of molecular biology and genomics. A working knowledge of Linux and R at the level of the Edinburgh Genomics Linux for Genomics and R for Biologists workshops.

 An image is more than a pretty picture.  It contains data that can be extracted and quantified.  During the five half-day course, students learn about the structure of an image –what a good image is- as well as different techniques to extract data in 2d, over time and in 3D.  The software that we’ll use are all freeware: Fiji, Ilastik, CellProfiler. 

Students get typical images, course notes and access to recording.

Instructors: Matthieu Vermeren