Courses and workshops at the Graduate Research School in Integrative Biology

Dates of the next course to be announced (1.5 ECTS)

This course’s aim is to provide a basic introduction to R, preparing students for using R in their own research. The course will use a combination of brief lectures and tutorials where the students will work on prepared problems. The last day of the course will include an open problems session where students are encouraged to bring their own data or analysis problems.

We will cover:

• basic R commands,
• basic data manipulation in R (different data structures),
• import and export of data,
• plotting commands (basic plotting and ggplot),
• functions for data summary and manipulation (for example computing means, variances, maxima,
  minima, and apply-functions) and
• time permitting – basic statistics.

Course leader: Johan Lindström

Dates of the course to be announced (1.3 ECTS)

This four-day course introduces the fundamental principles of building phylogenies using molecular data, as well as the latest techniques and programs in this field. The aims of this course are to introduce the theory and practice of phylogenetic inference from molecular data and to introduce some of the most used methods and computer programs. The emphasis will be on model-based methods using maximum likelihood and Bayesian inference, with a focus on DNA sequences as data. We will introduce programs such as IQTREE, MrBayes, as well as BEAST for timing of divergence analyses. The course will consist of lectures, demonstrations of computer programs, and independent projects on fully analysing an example dataset (either your own or given by the lecturer). The course is aimed at PhD students but is also suitable for researchers at any stage, including motivated MSc students.  

Course leaders: Jadranka Rota & Niklas Wahlberg

Dates of the course to be announced (3 ECTS)

This aim of this course is to teach students how to develop and perform systematic reviews and meta-analyses. These are valuable techniques for identifying broadscale patterns and trends in published literature. The course will provide practical training in how to perform systematic reviews and meta-analyses to a publishable standard, as well as how to assess the quality of other systematic reviews and meta-analyses.

This course will cover the basics of bioinformatic processing of sequence data on the UNIX/LINUX command line. The course will consist of both lectures and hands-on computer exercises. There will also be opportunities to discuss/plan the bioinformatic approaches you will use for your own sequencing data during the course. Course leader: Dag Ahrén.

This course will introduce key aspects of research data management through a combination of lectures and hands-on exercises. It is particularly suited for researchers looking to adopt a more systematic and reproducible approach to analysing and managing their research data. This course will be taught by NBIS with a number of places on the course reserved for IBIO students. Register no later than 11 June via the NBIS website.

This three-day workshop will cover key multivariate methodologies, interpretation of results and case studies. Learners will be given the opportunity to analyse their own data under the guidance and advice of instructors. Datasets will also be provided for those unable to bring their own data. The course will provide training in the use of the mixOmics R toolkit – the ‘go-to’ R package for multivariate omics data analysis. This course will be taught by Prof Kim-Anh Lê Cao from the University of Melbourne.

This five-day course will introduce the fundamental principles of phylogenetic comparative methods and their practical application through lectures and hands-on exercises in R. The course will cover topics such as plotting traits on phylogenies, character evolution modelling, ancestral state reconstruction and analysing data using linear phylogenetic models. Course leader: Charlie Cornwallis.

This two-day course will train learners in the theory and application of codon-based tests for detecting the signals of natural selection. Course leader: Emily O’Connor.