DOI: 10.5281/zenodo.7551294
title: Data for the course "Population Genomics" at Aarhus University

description: Datasets, conda environments and Softwares for the course "Population Genomics" of Prof Kasper Munch. The data is connected to the following repository: https://github.com/hds-sandbox/Popgen_course_aarhus. The original course material from Prof Kasper Munch is at https://github.com/kaspermunch/PopulationGenomicsCourse. <strong>Description</strong> The participants will after the course have detailed knowledge of the methods and applications required to perform a typical population genomic study. The participants must at the end of the course be able to: Identify an experimental platform relevant to a population genomic analysis. Apply commonly used population genomic methods. Explain the theory behind common population genomic methods. Reflect on strengths and limitations of population genomic methods. Interpret and analyze results of population genomic inference. Formulate population genetics hypotheses based on data The course introduces key concepts in population genomics from generation of population genetic data sets to the most common population genetic analyses and association studies. The first part of the course focuses on generation of population genetic data sets. The second part introduces the most common population genetic analyses and their theoretical background. Here topics include analysis of demography, population structure, recombination and selection. The last part of the course focus on applications of population genetic data sets for association studies in relation to human health. Curriculum The curriculum for each week is listed below. "Coop" refers to a set of lecture notes by Graham Coop that we will use throughout the course. Course plan Course intro and overview: Coop chapters 1, 2, 3, Paper: Genome Diversity Project Drift and the coalescent: Coop chapter 4; Paper: Platypus Exercise: Read mapping and base calling Recombination: Lecture: Review: Recombination in eukaryotes, Review: Recombination rate estimation Exercise: Phasing and recombination rate Population strucure and incomplete lineage sorting: Lecture: Coop chapter 6, Review: Incomplete lineage sorting Exercise: Working with VCF files Hidden Markov models: Lecture: Durbin chapter 3, Paper: population structure Exercise: Inference of population structure and admixture Ancestral recombination graphs: Lecture: Paper: Approximating the ARG, Paper: Tree inference Exercise: ARG dashboard exercises + Inference of trees along sequence Past population demography: Lecture: Coop chapter 4, Paper: PSMC, revisit Paper: Tree inference Exercise: Inferring historical populations Direct and linked selection: Lecture: Coop chapters 12, 13, revisit Paper: Tree inference Admixture: Lecture: Review: Admixture, Paper: Admixture inference Exercise: Detecting archaic ancestry in modern humans Genome-wide association study (GWAS): Lecture: Coop lecture notes 99-120 Exercise: GWAS quality control Heritability: Lecture: Missing heritability and mixed models review ; Coop Lecture notes Sec. 2.2 (p23-36) + Chap. 7 (p119-142) Exercise: Association testing Evolution and disease: Lecture: Genetic architecture review ; Article about "omnigenic" model ; Coop Lecture notes Sec. 11.0.1 (p217-221) Exercise: Estimating heritability