Session content

Monday – Classes from 09:30 to 17:30

 

 

Session 1-Introduction

 

-          Overview of the course program

 

-          Introduction on Landscape Genomics

 

-          Examples

 

 

Session 2 - Dataset

 

-          The environmental data

 

-          The genetic data

 

 

 

Tuesday – Classes from 09:30 to 17:30

 

 

Session 3-Environmental Data 1

 

-          GIS basics

 

-          Main environmental databases

 

-          Derived environmental variables

 

 

Session 4- Environmental Data 2

 

-          Environmental characterization of the samples

 

-          Point versus surface

 

-          Analysis of environmental diversity of samples

 

 

 

Wednesday – Classes from 09:30 to 17:30

 

 

Session 5- Genetic Data 1

 

-          Sequencing strategies

 

-          Data filtering

 

 

Session 6- Genetic Data 2

 

-          Spatial genetic variation

 

-          Population structure

 

 

 

Thursday – Classes from 09:30 to 17:30

 

 

Session 7-Statistical Analysis

 

-          Overview of statistical methods (univariate, multivariate, w/wo population structure)

 

-          samβada: logistic regression

 

 

Session 8-Interpreting Results

 

-          Spatial autocorrleation

 

-          Process samβada output in R

 

-          Validation of results

 

 

 

Friday – Classes from 09:30 to 17:30

 

 

Session 9- Planning a Landscape Genomics Experiment

 

-          Scale and Resolution

 

-          Sampling Design

 

 

Session 10-Conclusion

 

-          Take home messages

 

-          Question time