Precourse
Dardel compute resources
Computer exercises can be run on the Dardel HPC cluster at Stockholm maintained by PDC. However, you can also opt to run exercises on your own computer (see software installation below).
SUPR account
You will need a SUPR account to run exercises on Dardel. To access the time allocation you need to request access to the PGIP compute project pg_pgip_2025
at https://supr.naiss.se/project/ (heading Request Membership in Project
). The PDC support pages provide more details on how to apply for an account.
Dardel tutorials
Look at https://support.pdc.kth.se/doc/site_map/, in particular https://support.pdc.kth.se/doc/basics/quickstart/#how-to-log-in for information on how to connect to and work on Dardel.
Software installation
Although we will mainly work on Dardel, some exercises, notably the ones that utilise Jupyter notebooks, benefit from working in a local compute environment on your computer. We will use the pixi package manager to install necessary requirements from the package repositories bioconda and conda-forge.
To start using pixi, follow the install instructions to install. For a given exercise, software dependencies will be provided in a pixi manifest, an example of which is shown here:
[workspace]
channels = ["conda-forge", "bioconda"]
name = "variant-calling"
[dependencies]
fastqc = ">=0.12.1,<0.13"
Copy the contents to a file pixi.toml
in an appropriately named directory (e.g., variant-calling
), cd
to directory and activate environment with pixi shell
.
As mentioned above, you can choose to run all exercises on a local computer if you have pixi setup. You would then need to download relevant data, as detailed for each exercise. We have tried to make the exercise data sets small such that you can run them locally.
Suggested readings
Topics have been organized in modular units that consist of introductory slides and exercises. Some of the topics rely on concepts in population genetics and we recommend you at least skim these theoretical slides to be fully prepared for lectures.
Population genomics in practice provides a quick overview of population genomics. Although not required, it is recommended to briefly go through the following papers that will be discussed in the lecture:
See notes on usage for instructions how to view slides.
Resources
Literature
Lecture notes have been prepared based on the literature listed below.
Online
- Graham Coop’s notes on population genetics
- Comprehensive introduction to population genetics. Contains many biological examples and code snippets. (Graham Coop, 2020).
- Jonathan Pritchard’s introduction to human population genetics.
- Although focussing more on human data, contains excellent explanations of statistical concepts and lots of instructive drawings. (Pritchard, n.d.)
- Joachim Hermisson’s notes on mathematical population genetics
- Introduction to mathematical population genetics (Hermisson, 2017, 2018).
Books
- Population Genetics: A Concise Guide
- John Gillespie’s short but excellent introduction to population genetics (Gillespie, 2004).
- Molecular Population Genetics
- A more recent introduction to population genetics with more focus on the analyses of sequencing data (Hahn, 2019).
- Molecular Evolution and Phylogenetics
- Overview of molecular evolution and population genetics, and also phylogenetics (Nei & Kumar, 2000).
- Mathematical Population Genetics I
- A great reference when it comes to the mathematical treatment of population genetics (Ewens, 2004).
- Principles of Population Genetics
- A comprehensive textbook covering most topics of population genetics (Hartl & Clark, 1997).
- Elements of Evolutionary Genetics
- Introduction to evolutionary genetics (Charlesworth & Charlesworth, 2010).
- Evolution
- Great comprehensive textbook covering evolution (Barton et al., 2007).
- Coalescent Theory: An Introduction
- A great introduction to coalescent theory (Wakeley, 2008).
- Gene Genealogies, Variation and Evolution: A Primer in Coalescent Theory
- Alternative introduction to coalescent with more focus on the Wright-Fisher model (Hein et al., 2005).