registrations are now open for the 2nd edition of the Physalia-course "Population genomic inference from low-coverage whole-genome sequencing data", which will be delivered remotely in October (11th-14th).
nstructors: Dr. Nina Overgaard Therkildsen (Cornell University, USA) 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.
Here you can find the full list of our courses and Workshops: https://www.physalia-courses.org/courses-workshops/
Should you have any questions, please feel free to contact us: email@example.com