Landscape genomics training (AUS)

Pop. and Landscape genomics workshop, Canberra 2014

Contact:

 

Session notes and slides :

Course (.pdf document)

Course – Slides (.pdf document)

Practical work (.pdf document)

 

The practical work on landscape genomics uses data on Loblolly pine (Pinus taeda) sampled in the US by the Eckert lab http://eckertdata.blogspot.ch/, (Eckert et al., 2010; Eckert et al., 2010). The purpose is to compute association models between SNPs data and environmental variables that will be downloaded or computed in a GIS.

We will use a GIS software mostly to visualize data (Quantum GIS), another one to produce environmental variables from Digital Elevation Models (DEMs) (SAGA GIS), and a third one to compute spatial statistics (OpenGeoda).

Quantum GIS can be found here:

 

SAGA GIS can be found here:

OpenGeoda can be found here:

 

Landscape Genomics software  

We will use are SamBada – based on multivariate logistic regressions -, LFMM, which considers population structure, and Admixture which computes membership coefficients to populations for each individual.

 

We will also use R for statistical analyses. You can install a modified GUI for R such as R studio

Following packages should be installed as well:

  • RSAGA

 

Genetic Data

We transformed genetic data to PLINK format in both binary (BED) and ordinary (PED) format.

Data can be found here:

 

Environmental Data

Sampling locations with aridity variables can be found here:

Several individuals have identical coordinates. In the purpose of visualizing them all in a GIS, we suggest modified coordinates.

 

Examples for Spatial Autocorrelation

 

 

We will use climatic variables from Worldclim datasets.

In the interest of time, we have created a subset for our study zone that you can download from our server : WorldClim_Subset.zip

Original datasets can be downloaded either by thiles or for the entire world:

 

DEMs can be found on Earth Explorer (subscription is mandatory before download):

If you dont want to sign up on EarthExplorer, you can download the DEM here

 

Recommended readings

Papers regarding practical work datasets can be found on Eckert’s blog:

 

We also recommend reading papers and documentation related to the software we will use

SamBada

LFMM

Admixture