Run biennially at the Genome Campus (and jointly with EMBL-EBI) this hands-on computational course aims to provide early-career stage researchers with the theoretical knowledge and practical skills to carry out molecular evolutionary analyses on sequence data. Instructors teaching molecular evolution may also benefit from this course by refreshing their knowledge of cutting-edge analytical methods in the field.

In addition, the course will offer a unique opportunity for direct interaction with some of the world-leading scientists and authors of famous analysis tools in Evolutionary Bioinformatics.

The demand for such training is large and growing, as are the sequence databases and researchers’ awareness of the important insights that can be gained from phylogenetic and molecular evolutionary techniques.

All details for this event can be found on the Connecting Science Courses and Conferences website.

Who is this course for?

Experience from previous years has led to preference being given to candidates who:

• are doctoral candidates in the early to middle stages of their thesis research
• already have some familiarity with phylogenetic methods (i.e. have already used some of the relevant tools)
• have already collected/assembled a molecular sequence dataset to analyze in their work
• have experience of working in a Unix/Linux command-line environment

We will also select a small number of participants that already work in bioinformatics labs, to intensify collaboration between early career stage biologists and bioinformaticians. Applicants from labs with a strong focus on computational molecular evolution methodology need to carefully outline their motivation for attending the course in this context, since they have ready access to expert supervision and are likely to be very skilled already in the topics we teach, or are in the course of becoming very skilled therein.

The course is also suitable for established researchers who would like to refresh their memory of modern statistical methods for phylogenetic analysis of genomic sequence data and to interact with developers of such methods.

What will I learn?

Learning outcomes

The overall objective is to raise the standard of research that uses methods and approaches from the field of molecular evolution, by providing high-quality, in-depth, face-to-face training on this topic for as many researchers as possible. By the end of the course participants should be able to:

• Have an improved theoretical understanding of relevant methods, thus improving their ability to critically interpret and apply relevant techniques to their studies
• Interpret evolutionary trees and recognise / discuss the power of molecular phylogenies for understanding real-world biological questions, relating to evolutionary history, current-day biodiversity and future diversification of living organisms
• Browse, query and extract genome sequence data from public databases, and create multiple sequence alignments.
• Employ appropriate bioinformatics skills that also allow for the analysis of large genome-scale datasets, including command line use of specialist software, simple scripting, and compiling programs and submitting jobs on multi-core servers and compute clusters.
• Select and apply appropriate commonly used phylogenetic software packages (such as PhyML, RAxML, PAML, MrBayes, BEAST) to infer phylogenetic trees, estimate divergence times, and test phylogenetic hypotheses.
• Understand and explain the underlying principles of major phylogenetic methods such as distance matrix-based, maximum likelihood, and Bayesian methods, including the MCMC method.
• Understand and explain the use of Markov models of nucleotide, amino acid and codon substitution, hypothesis testing using the likelihood ratio test, coalescent and multispecies coalescent models in species tree estimation and species delimitation.
• Apply likelihood ratio tests to infer the existence and location of molecular adaptation affecting protein-coding genes.

Course content

The extensive programme comprises a mixture of lectures and computer practicals covering the following topics:

• Data retrieval and assembly
• Alignment techniques
• Phylogeny reconstruction (including maximum likelihood and Bayesian methods)
• Hypothesis testing
• Population genetics approaches
• Protein and nucleotide sequence analysis, including NGS data (Please note however that the course focuses on NGS analyses for molecular evolution, we do not cover traditional NGS analyses e.g., QC, read mapping, variant calling, assembly etc.).

All details for this event can be found on the Connecting Science Courses and Conferences website.