Monday. Classes from 2 to 8 pm Berlin time

We will discuss the rationale behind the use of low-coverage whole-genome sequencing for population genomic inference. We will then walk through typical workflows for going from sample to raw sequencing data, and from raw sequencing data to processed alignment files ready for downstream analysis.

Tuesday. Classes from 2 to 8 pm Berlin time

We will introduce the concept of sequence data uncertainty and genotype likelihoods. We will then discuss the currently available software for population genetic analysis from low-coverage data. Finally, we will explore how to estimate allele frequencies and perform SNP calling with ANGSD.

Wednesday. Classes from 2 to 8 pm Berlin time

We will explore how to infer population structure and demographic parameters from low-coverage sequencing data using ANGSD. We will focus on performing principal component analysis and admixture inference. We will also discuss how to estimate the site frequency spectrum and inbreeding coefficients.

Thursday. Classes from 2 to 8 pm Berlin time

We will explore how to estimate summary statistics to detect signals of natural selection. Specifically, we will explain the protocol for estimating genetic variation indexes at the genome-wide level and in sliding-windows with ANGSD. We will focus on both single-population metrics, such as Tajima’s D and linkage disequilibrium, and multi-population metrics, such as FST and PBS.