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 Cumbare, 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 accommodation, 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 Practicum 3: Student Presentations Please send inquiries to oliverhoo...@prstatistics.com or visit the website *www.prstatistics.com* <http://www.prstatistics.com/> Please feel free to distribute this information anywhere you think suitable Upcoming courses - email for details oliverhoo...@prstatistics.com 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) -- MORPHMET may be accessed via its webpage at http://www.morphometrics.org --- 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 to morphmet+unsubscr...@morphometrics.org.
