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Analysing Environmental Adaptation Using Landscape Genomics in R (EDAP01)

15 July 2019 - 19 July 2019

£275.00 - £510.00

Course Overview:

Local adaptation to climate and other environmental drivers increasingly is being studied at the molecular level using high-throughput sequencing methods, with applications spanning both model and non-model organisms. At the same time, statistical tools for modeling and mapping patterns of biodiversity have seen increasing application, including to the challenge of understanding the drivers of spatial variation in adaptive genomic variation and mapping these patterns under current and future climate. This 5-day course will provide the skill set necessary to analyze sequence data for signatures of natural selection and to apply spatial modeling techniques to these patterns to quantify and map population-level genetic variation using two spatial modelling algorithms – Generalized Dissimilarity Modelling (GDM) and Gradient Forest (GF).

The course will include introductory lectures, instruction on using the Linux command line for manipulation of genomic data, guided computer coding in R, and exercises for the participants, with an emphasis on visualization and reproducible workflows. Portions of each day will be allotted for students to work through their own datasets with the instructors.

This course is intended for research scientists, postdoctoral researchers, and graduate students interested in learning how to analyze genomic data for signals of adaptation using population genetic tools and the application of spatial modeling understanding and mapping landscape genomic patterns in R.

After successfully completing this course students will:

  • Understand the theory and techniques for detecting signals of natural selection using genomic data, focusing on multi-population and landscape approaches
  • Understand the statistical underpinnings of spatial modeling methods (GDM and GF) for analyzing and mapping adaptive genomic variation
  • Be able to develop, evaluate and apply GDM and GF for quantifying and mapping spatial genetic patterns
  • Estimate population-level vulnerability to climate change
  • Students are highly encouraged to bring their own data to the course.

Intended Audience

Any researchers (from postgraduate students to senior investigators) interested in the use of spatial modelling for quantifying and visualizing patterns of biodiversity, including those in applied fields and basic science.

Venue – PR statistics head office, 53 Morrison Street, Glasgow, G5 8LB – Google map

Availability – 25 places

Duration – 5 days

Contact hours – Approx. 35 hours

ECT’s – Equal to 3 ECT’s

Language – English


• COURSE ONLY – Includes lunch and refreshments and welcome meal Monday evening.
• ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, refreshments and welcome dinner Monday evening. Self-catering facilities are available in the accommodation. Accommodation is multiple occupancy (max 3-4 people) single sex en-suite rooms. Arrival Sunday 14th July (between 17:00-21:00) and departure Friday 19th July PM (accommodation must be vacated by 09:15).

To book ‘COURSE ONLY’ with the option to add the additional ‘ACCOMMODATION PACKAGE’ please scroll to the bottom of this page.

Other payment options are available please email oliverhooker@prstatistics.com

PLEASE READ – CANCELLATION POLICY: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees (and accommodation fees if booked through PR statistics) will be credited. However, PR statistics will not be held responsible/liable for any travel fees, accommodation costs or other expenses incurred to you as a result of the cancellation. Because of this PR statistics strongly recommends any travel and accommodation that is booked by you or your institute is refundable/flexible and to delay booking your travel and accommodation as close the course start date as economical viable.


Dr. Matt Fitzpatrick

Aki Laruson

Teaching Format
Course Programme


15 July 2019
19 July 2019
£275.00 - £510.00


PR statistics head office
53 Morrison Street
Glasgow, Scotland G5 8LB United Kingdom
+ Google Map


24 available
EDAP01 'COURSE ONLY'£510.00‘COURSE ONLY’ (INC VAT@20%) Places 1-25
23 available