Dear all,
We are excited to announce that registrations are now open for our upcoming online course (5th edition) "Population Genomic Inference from Low-Coverage Whole-Genome Sequencing Data" taking place from October 21-24.
Course website: https://www.physalia-courses.org/courses-workshops/course64/
Course Overview: This course offers a cost-effective approach to survey genome-wide variation at a population scale using low-coverage sequencing. Participants will learn how to navigate the challenges of high genotyping uncertainty through probabilistic frameworks, essential for accurate population genomic inference.
Key topics include:
- Workflows centered around genotype likelihoods for whole-genome and reduced representation studies.
- Methods and algorithms in the ANGSD software package and related programs.
- Best-practice guidelines for processing and analyzing low-coverage sequencing data.
Target Audience: This course is ideal for researchers with experience in next-generation sequencing (NGS) (e.g., exome, RAD, pooled sequencing) who are interested in low-coverage whole-genome sequencing. It is also suitable for those seeking an introduction to the ANGSD software and its probabilistic framework.
Prerequisites: Participants should have a basic background in population genomics and familiarity with NGS data. Knowledge of UNIX-based command line and R is advantageous. Participants without prior experience in Unix and R should complete suggested tutorials beforehand, as the course will not cover these environments in detail.
Course Outcomes:
By the end of the course, participants will:
- Understand the use of whole-genome sequencing for population genomics.
- Recognize the challenges and statistical frameworks of low-coverage sequencing data.
- Be able to build bioinformatic pipelines for various population genomic analyses using ANGSD/ngsTools/Atlas.
Teaching Format: The course includes interactive lectures, small exercises, and longer independent practical sessions each day. Data for exercises will be provided.
