17-21 October 2022
Due to the COVID-19 outbreak, this course will be held online
Reduced representation genome sequencing methods are revolutionizing evolutionary analyses of non-model organisms. Several data generation and data analysis protocols have been developed to generate thousands of sequence variants in hundreds of individuals at relative low cost and speed. In this course, we will introduce the different approaches for obtaining reduced representation genome sequencing data and will specially focus on the data analysis using Stacks. We will cover all necessary steps to obtain genome variants from short read data that are informative for population genetics, phylogenetic and association studies.
The course will be delivered over the course of five days. Each day will include an introductory lecture with class discussion of key concepts. The remainder of each day will consist of practical hands-on sessions. These sessions will involve a combination of both mirroring exercises with the instructor to demonstrate a skill as well as applying these skills on your own to complete individual exercises. After and during each exercise, interpretation of results will be discussed as a group.
This course is
aimed at researchers and technical workers who are or will be generating and/or analyzing reduced representation genome sequencing data (RAD-seq, ddRAD, 2bRAD, GBS,…). Examples demonstrated in
this course will involve primarily non-model organisms with and without draft reference genomes available and examples of applications of this data type for different purposes will be
Attendees should have a background in biology. We will dedicate one session to some basic and advanced Unix concepts. Attendees should have also some familiarity with genomic data such as that arising from NGS high-throughput sequencers.
Monday - Classes from 2 to 8 pm Berlin time
Lecture 1 – Introduction to high-throughput reduced representation data
Lab 1 – Computer environment set up and introduction to UNIX
Lab 2 – High-throughput data quality assessment
> 30 days before the start date = 30% cancellation fee
< 30 days before the start date= No Refund.
Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.