Landscape Genomics Berlin

Introduction

Landscape genomics is an emerging research field that studies how genetic diversity distributes across space and how environmental features can modify this structure through local adaptation. In this workshop, students will learn the basics of this approach and train using state of the art methods.

Theoretical background

Presentations

1.1 Presentation GIS Lab EPFL
1.2 Programme
1.3 Landscape genetics
1.4 Landscape genomics
1.5 Examples (case studies)
2.1 GIS basics
2.2 Environmental data 1
3.1 Environmental data 2
3.2 Environmental data 3
4.1 Spatial overlay – spatial coincidence
4.2 Multivariate characterization of samples
5.1 Sequencing and types of molecular markers
6.1 Spatial autocorrelation
6.2 Introduction to Geoda
7.1 Sambada software&logistic regression
9.1 Sampling design
10.1 Conclusion
 

Data

• Exercise 1 data
• Exercise 2 data
• Exercise 3 data
• Exercise 4 data
• Exercise 5 data
  • Code StSn
• Exercise 6 data
• Exercise 7 data (without SamBada output)
  • SamBada output
• Exercise 8 data

Exercises

• Exercise 1
  • Solution ex 1
• Exercise 2
  • Solution ex 2
• Exercise 3
  • Solution ex 3
• Exercise 4
  • Solution ex 4
• Exercise 5
  • Solution ex 5
• Exercise 6
  • Solution ex 6
• Exercise 7
  • Solution ex 7
• Exercise 8
  • Sampling Examples
  • R Code Example

Software

• QGIS – version 2.18.13 (LTR)
• R – latest release is v3.4.2
• R studio (RStudio requires R 3.0.1+)
• Sambada
• Geoda – version 1.12

Papers

Links

Alignment search tools

• GenBank (NCBI)
• Blast (NCBI)
• ENSEMBL
• SNPchimp

Environmental variables

• Global Land Cover Characteristics Data Base Version 2.0, get data via http://earthexplorer.usgs.gov/
• USGS Earth Explorer http://earthexplorer.usgs.gov/ Raster Remote sensing data (Aerial images, DEMs, infrared images)
• WorldClim http://www.worldclim.org/ Raster Climate data (past, current and future)
• Diva GIS http://www.diva-gis.org/Data Raster, Vector Global climate data, biodiversity and crop collection data
• Sentinel Satellite Data https://scihub.copernicus.eu/dhus Raster 10-m resolution satellite data Sentinel 2 data with 11 spectral bands, Synthetic aperture radar
• Open Street Map https://www.openstreetmap.org Vector Crowd sourced vector data. (Road network, land use, buildings etc.)
• Global Biodiversity Information Facility http://www.gbif.org/ Vector Information on biodiversity of 1.6 million species, collected over three centuries
• Map of Life http://mol.org/ Vector Species range map
• UNEP http://geodata.grid.unep.ch/ Vector Data on environment, climate, emissions
• FAO http://www.fao.org/geonetwork/srv/en/main.home Vector Database containing inter-disciplinary information about biodiversity
• Worldwide Global Forest Change https://earthenginepartners.appspot.com/science-2013-global-forest Raster Time-series analysis of Landsat images characterizing forest extent and change
• NASA Earth Observation https://neo.sci.gsfc.nasa.gov/ a repository of a wide range of products derived from satellite remote sensing, describing atmosphere, energy, land and ocean.
• Copernicus Marine Environment Monitoring Service http://marine.copernicus.eu/ a repository of a wide range of products related to oceans conditions.