GeometricMorphometricsUsingR.DeanAdams.Scotland.Jun5-9

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GeometricMorphometricsUsingR.DeanAdams.Scotland.Jun5-9

Oliver Hooker
Geometric Morphometrics Using R (GMMR01)

This course is being delivered by Prof. Dean Adams, Prof. Michael
Collyer and Dr. Antigoni Kaliontzopoulou

This course will run from 5th - 9th June 2017 at Millport Field centre
on the Isle of Cumbre, Scotland. Please note that although the course is
held on an island it is extremely accessible and easy to reach using
public transport.

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
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 workshop.

Course cost is £520 for students and academic staff and £630 for
people working in industry.
Accommodation package available for £275, includes all meals and
refreshments.

Course Programme

Sunday 5th Meet at Millport field centre at approximately 18:30.

Monday 6th – Classes from 09:00 to 18:001:
1: Morphometrics: History, Introduction and Data Types
2: Review of matrix algebra and multivariate statistics
3: Superimposition
4: Software demonstration and lab practicum

Tuesday 7th – Classes from 09:00 to 18:00
1: Shape spaces, shape variables, PCA
2: GPA with semi-landmarks
3: Shape covariation
4: Software demonstration and lab practicum

Wednesday 8th – Classes from 09:00 to 18:00
1: Phylogenetic shape variation
2: Group Differences & Trajectory Analysis
3: Allometry
4: Software demonstration and lab practicum

Thursday 9th – Classes from 09:00 to 18:00
1: Assymetry
2: Missing Data
3: Integration and Modularity
4: Disparity
5: Software demonstration and lab practicum

Friday 10th – Classes from 09:00 to 16:00
1: Future Directions
2: Lab Pacticum
3: Student Presentations

Please send inquiries to [hidden email] or visit the
website www.prstatistics.com

Please feel free to distribute this information anywhere you think
suitable

Upcoming courses - email for details [hidden email]
1. ADVANCING IN STATISTICAL MODELLING USING R (December 2016, April
2017, December 2017
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr05/
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr06/
2. SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (November 2016, July
2017)
http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r-spae04/
3. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R
(February 2017)
http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm03/
4. GENETIC DATA ANALYSIS USING R (TBC)
5. BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS (July 2017)
http://www.prstatistics.com/course/bioinformatics-for-geneticists-and-biologists-bigb02/
6. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS
(November 2017)
7. INTRODUCTION TO STATISTICS AND R FOR BIOLOGISTS (April 2017)
http://www.prstatistics.com/course/introduction-to-statistics-and-r-for-biologists-irfb02/
8. INTRODUCTION TO PYTHON FOR BIOLOGISTS (TBC)
9. TIME SERIES MODELS FOR ECOLOGISTS AND CLIMATOLOGISTS (TBC)
10. ADVANCES IN MULTIVAIRAITE ANALYSIS OF SPATIAL ECOLOGICAL DATA (April
2017)
11. ADVANCES IN DNA TAXONOMY (TBC)
12. INTRODUCTION TO BIOINFORMATICS USING LINUX (TBC)
13. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING
http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm02/
14. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (TBC)
15. PHYLOGENETIC DATA ANALYSIS USING R (TBC)
16. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R
(January 2017)
http://www.prstatistics.com/course/model-base-multivariate-analysis-of-abundance-data-using-r-mbmv01/
17. ADVANCED PYTHON FOR BIOLOGISTS (February 2017)
http://www.prstatistics.com/course/advanced-python-biologists-apyb01/
18. NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March)
http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/
19. GEOMETRIC MORPHOMETRICS USING R (June)
http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/
20. INTRODUCTION TO METHODS FOR REMOTE SENSING (July 2017)
21. ECOLOGICAL NICHE MODELLING (October 2017)
22. ANIMAL MOVEMENT ECOLOGY (TBC)

--
Oliver Hooker PhD.
PR statistics

3/1
128 Brunswick Street
Glasgow
G1 1TF

+44 (0) 7966500340

www.prstatistics.com
www.prstatistics.com/organiser/oliver-hooker/

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