Course : LANDSCAPE GENOMICS (3rd edition)
When: 25th-29th November 2019
Where: Free University (FU) Berlin (Gemany)
Application deadline is: October 20th, 2019. Attendees are seated on a first-come, first-served basis.
1) Dr. Stèphane Joost (Lab of Geographic Information Systems (LASIG), EPFL, Lausanne, Switzerland)
2) Dr Elia Vajana (Lab of Geographic Information Systems (LASIG), EPFL, Lausanne, Switzerland)
The course will provide an overview of the type of dataset that can be used for a landscape genomics analysis. Firstly, students will learn how to obtain environmental data from publicly available databases, how to process it with Geographic Information Systems (GIS) and how to use the latter to produce indicators able to describe the characteristics of the landscape. Next, we will discuss the different approaches to obtain genetic data and subsequently show how to study genetic variation and population structure across space in the R environment. We will give an overview of the different statistical approaches to study local adaptation, and the participants will be trained in using two of them, Sambada and LFMM. The course will also cover the critical task of the interpretation and validation of the results. Finally, the course will consider the crucial aspects and good habits to account for when planning a landscape genomics experiment (e.g. sampling design).
Targeted Audience & Assumed Background
This course is aimed at all biologists, ecologists, geneticists, veterinarians that want to implement the landscape genomics approach in their own studies of evolutionary biology and conservation. Even though the course is not intended for a specialized audience, basic knowledge in evolutionary biology and population genetics would help. Students will learn how to use GIS, but basic computer skills are desirable (e.g. in the R environment). A basic understanding of statistics is also necessary.
The course is organized in ten learning sessions. During the first two sessions, the course will provide a contextualization of the research field. Then, students will be guided through a landscape genomics experiment with sessions that couple brief theoretical introductions with practical work.
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