Geometric morphometrics using R (GMMR02)

Please feel free to share!

This course will be delivered by Dean Adams, Mike Collyer and Antigoni 
Kaliontzopoulou in Glasgow City Centre for the 30th September - 4th October 

You will recognise these names from answering many of the questions on 
morphmet and as the developers of Geomorph - you could not ask for a better 
combinations of instructors!
Course overview: The field of geometric morphometrics (GM) is concerned 
with the quantification and analysis of patterns of shape variation, and 
its covariation with other variables. Over the past several decades these 
approaches have become a mainstay in the field of ecology, evolutionary 
biology, and anthropology, and a panoply of analytical tools for addressing 
specific biological hypotheses concerning shape have been developed. The 
goal of this is to provide participants with a working knowledge of the 
theory of geometric morphometrics, as well as practical training in the 
application of these methods.
The course is organized in both theoretical and practical sessions. The 
theoretical sessions will provide a comprehensive introduction to the 
methods of landmark-based geometric morphometrics, which aims at providing 
the participants with a solid theoretical background for understanding the 
procedures used in shape data analysis. Practical sessions will include 
worked examples, giving the participants the opportunity to gain hands-on 
experience in the treatment of shape data using the R package geomorph. 
These sessions focus on the generation of shape variables from primary 
landmark data, the statistical treatment of shape variation with respect to 
biological hypotheses, and the visualization of patterns of shape variation 
and of the shapes themselves for interpretation of statistical findings, 
using the R language for statistical programming. While practice datasets 
will be available, it is strongly recommended that participants come with 
their own datasets.
Note: Because this is a geometric morphometrics workshop in R, it is 
assumed, and is in fact required, that participants have some working 
knowledge in R. The practical sessions of the course will focus on GM-based 
analyses, and not basic R user-interfacing. It is therefore strongly 
recommended that participants refresh their R skills prior to attending the 
Monday 30th – Classes from 09:30 to 17:30
1: Morphometrics: History, Introduction and Data Types
2: Review of matrix algebra and multivariate statistics
3: Superimposition
4: Software demonstration and lab practicum
Tuesday 1st – Classes from 09:30 to 17:30
1: Shape spaces, shape variables, PCA
2: GPA with semilandmarks
3: Shape covariation
4: Software demonstration and lab practicum
Wednesday 2nd – Classes from 09:30 to 17:30
1: Phylogenetic shape variation
2: Group Differences & Trajectory Analysis
3: Allometry
4: Software demonstration and lab practicum
Thursday 3rd – Classes from 09:30 to 17:30
1: Assymetry
2: Missing Data
3: Integration and Modularity
4: Disparity
5: Software demonstration and lab practicum
Friday 4th – Classes from 09:30 to 16:00
1: Future Directions
2: Lab Practicum
3: Student Presentations


Check out our sister sites, (Ecology and Life Sciences) (Bioinformatics and data science) (Behaviour and cognition) 
Oliver Hooker PhD.
PR statistics

2018 publications - 

Alternative routes to piscivory: Contrasting growth trajectories in brown 
trout (Salmo trutta) ecotypes exhibiting contrasting life history 
strategies. Ecology of Freshwater Fish. DOI to follow

Phenotypic and resource use partitioning amongst sympatric lacustrine brown 
trout, Salmo trutta. Biological Journal of the Linnean Society. DOI 

MORPHMET may be accessed via its webpage at
You received this message because you are subscribed to the Google Groups 
"MORPHMET" group.
To unsubscribe from this group and stop receiving emails from it, send an email 

Reply via email to