ONLINE COURSE – Landscape genetic data analysis using R (LNDG04) This course will be delivered live
24 May 2021 - 28 May 2021£490.00
The term ‘landscape genetics’ has been applied studies that integrate ecological context and intervening landscape into population genetic analyses of contemporary processes such as gene flow and migration. This course will cover the basics of both quantitative landscape ecology and population genetics, focusing on how we develop and evaluate spatial/genetic analyses using the R platform.
This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
TIME ZONE – Eastern Standard Time – however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional 1/2 days support after the official course finish date (please email email@example.com for full details or to discuss how we can accommodate you).
This course is suitable for graduate students, postdoctoral researchers, and primary investigators interested in learning how to integrate landscape ecological and population genetic tools using the R software.
Venue – Delivered remotely
Time zone – Eastern Standard Time
Availability – 24 places
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
Other payment options are available please email firstname.lastname@example.org
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 email@example.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 will be credited.
Prof. Rodney Dyer
Works at –
Teaches – Landscape Genetics using R (LNDG)
Prof Rodney Dyer is…
There will be morning lectures based on the modules outlined in the course timetable. In the afternoon there will be practicals based on the topics covered that morning. Data sets for computer practicals will be provided by the instructors, but participants are welcome to bring their own data.
Assumed quantitative knowledge
A basic understanding of statistical concepts. Specifically, generalised linear regression models, statistical significance, hypothesis testing.
Assumed computer background
Familiarity with R. Ability to import/export data, manipulate data frames, fit basic statistical models & generate simple exploratory and diagnostic plots.
Equipment and software requirements
A laptop/personal computer with a working version or R and RStudio installed. R and RStudio are supported by both PC and MAC and can be downloaded for free by following these links.
It is essential that you come with all necessary software and packages already installed (you will be sent a list of packages prior to the course) internet access may not always be available.
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK firstname.lastname@example.org
Monday 14th – Classes from 09:30 to 17:30
Module 1: Spatial & Ecological Data.
Installation & configuring R & RStudio
Acquiring spatial data, projections, and visualization
Vector and raster data
Tuesday 25th – Classes from 09:30 to 17:30
Module 2: Genetic markers and basic analyses
Genetic markers and sampling
Genetic distance, diversity, and structure
Ordination techniques based upon genetic markers
Wednesday 26th – Classes from 09:30 to 17:30
Module 3: Integrating spatial and genetic data
Barrier detection & population division
Mantel and distance regressions
Remote sensing – LiDAR and Hyperspectral data
Thursday 27th – Classes from 09:00 to 17:00
Module 4: Integrating spatial and genetic data
PCMN & Redundancy
Friday 28th – Classes from 09:30 to 16:00
Module 5: Adaptive Genetic Variance
Outliers & gradients
Quantitative genetics, why we should care.