syllabus.qmd

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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.

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## Covered topics

- 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

## Learning objectives

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

## Requirements

- 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

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