ONLINE course "Population genomic inference from low-coverage whole-genome sequencing data"

When: 19-22 October 2020

Instructors: Dr. Nina Overgaard Therkildsen (Cornell University, US) and Dr. Matteo Fumagalli (Imperial College London, UK)

Course website: https://www.physalia-courses.org/courses-workshops/course64/

In this course, we will explore workflows and the underlying rationale behind producing, processing, and analyzing low-coverage sequencing data for population genomic inference. Given that most species have insufficient reference data to allow reliable genotype imputation, we will focus on genotype likelihood-based methodology that can be applied to any system. We will primarily cover methods and algorithms implemented in the ANGSD software package and associated programs, providing best-practice guidelines and discussion of how participants can make maximal use of low-coverage whole genome re-sequencing data for their studies.

The course is aimed at researchers who might have previous experience with next generation sequencing (NGS) data (e.g. exome/RAD/pooled sequencing) and wish to explore the potential for using low-coverage whole-genome sequencing for their studies.

All hands-on exercises will be run in a Linux environment on remote servers. Statistical analyses and data visualization will be run in R.

Should you have any questions, please feel free to contact us: info@physalia-courses.org