The basics

As the workshop heavily relies on UNIX and VCF-files, you can find introductory tutorials below:

• Basic UNIX tutorial: Evomics unix tutorial
  On the first day of the workshop, you can join the workshop team for a UNIX Primer (optional).
• VCF-file tutorial: First steps in genomic data analysis
  A basic tutorial on the first steps in population genomic data analyses: exploring the Variant Call Format (VCF), quality filtering, and Principal Component Analysis (PCA). We taught this exercise in 2019 and 2020 but had mixed feedback since many participants were already familiar with these analyses. In 2022, we therefore removed it from the schedule. Should you have no prior experience with VCF files and basic VCF-file analyses, please have a look at this tutorial and just drop Julia an email to request the example data and the plotting script.

 

General background reading

If during your preparation or in the workshop you find the wish to have additional background theory or refresh your knowledge on population genetics theory, there is the following online resource on general population genetics, with R code examples:

• Graham Coop (2019) Population and quantitative genetics

 

Additional reading

For the interested: you can find below, per topic, reviews and articles suggested by the faculty and workshop team (don’t worry about reading everything):
 

Bayesian inference

Easy-to-follow visual explanations of likelihood and Bayesian inference can be found in Paul Lewis’ phyloseminars available on Youtube:

• Lewis (2018) Primer part 1 (introduction of likelihood starts at minute 19)
• Lewis (2018) Primer part 3a

 

Natural selection / adaptation

Two reviews on the identification of signals of selection:

• Nielsen et al. (2005) Approaches for identifying targets of positive selection
• Hohenlohe, Phillips and Cresko (2010) Using population genomics to detect selection in natural populations: key concepts and methodological considerations

 
A guide to landscape genomics:

• Rellstab et al. (2015) A practical guide to environmental association analysis in landscape genomics

 

Genome-wide genealogy inference

The paper on Relate by Speidel et al. and a commentary by Kelley Harris:

• Speidel, Forest, Chi, Myers (2019) A method for genome-wide genealogy estimation for thousands of samples
• Harris (2019) From a database of genomes to a forest of evolutionary trees

 

The multi-species coalescent

A review on the model and a paper on tree discordance:

• Degnan and Rosenberg (2009) Gene tree discordance, phylogenetic inference and the multispecies coalescent
• Wang and Hahn (2018) Speciation genes are more likely to have discordant gene trees

 

Measuring divergence and gene flow between species

Examples of genome-wide analyses of speciation and gene flow, using Heliconius butterflies as a model system:

• Moest et al. (2020) Selective sweeps on novel and introgressed variation shape mimicry loci in a butterfly adaptive radiation
• Martin et al. (2013) Genome-wide evidence for speciation with gene flow in Heliconius butterflies

 

Structural Variation

Reviews providing frameworks to study SVs:

• Mérot et al. (2020) A Roadmap for Understanding the Evolutionary Significance of Structural Genomic Variation
• Berdan et al. (2021) Unboxing mutations: Connecting mutation types with evolutionary consequences

 
Examples of SV analyses in mammals and birds:

• Kapusta et al. (2017) Dynamics of genome size evolution in birds and mammals
• Weissensteiner et al. (2020) Discovery and population genomics of structural variation in a songbird genus

 

Machine Learning

Review introducing machine learning and how it can be used in population genetics:

• Schrider and Kern (2018) Supervised Machine Learning for Population Genetics: A New Paradigm

 

Simulation inference

Publication describing the model behind msprime and use cases:

• Baumdicker et al. (2022) Efficient ancestry and mutation simulation with msprime 1.0