Syllabus

The aim of this workshop is to provide an introduction to commonly used methods in population genomics. As the focus of the course is on hands-on work, the topics have been designed to cover the fundamental analyses that are common in many population genomics studies. The course consists of lectures and exercises, with a focus on the practical aspects of analyses. Whereas lectures introduce some background theory, their primary aim is to set the stage for accompanying exercises.

  • Foundations of population genetics
  • Introduction to simulation and the coalescent
  • Basics of variant calling
  • Variant filtering and sequence masks
  • Characterization and intepretation of DNA sequence variation
  • Calculation and interpretation of summary statistics from variation data
  • Investigating population structure with admixture modelling and principal component analyses
  • Demographic modelling using sequentially Markovian coalescent models and linkage disequlibrium
  • Selection scans

Upon completion of this course, you will be able to:

  • describe the different forces of evolution and how they influence genetic variation
  • understand and interpret genealogical trees and how they relate to genetic variation data
  • describe the basics of the coalescent
  • perform simple coalescent simulations with msprime
  • run simple SLiM forward simulation models
  • describe and run the steps of a variant calling pipeline, including quality control of raw reads, read mapping, and variant calling
  • know how and when to filter raw variant calls using manual coverage filters
  • describe and calculate nucleotide diversity from variation data
  • analyze population structure with admixture modelling and dimensionality reduction methods
  • perform demographic modelling with sequential Markovian coalescent models
  • describe methods that identify regions undergoing adaptation and selection
  • run selection scans, score identified regions and interpret findings in the context of genome annotations
  • Basic knowledge in R or Python
  • Basic knowledge of variant calling, or the equivalent of NBIS course “Introduction to Bioinformatics using NGS data”
  • Basic knowledge of population genetics
  • Basic understanding of frequentist statistics
  • A computer

Desirable:

  • Experience with analysis of NGS and other omic data