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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 [log in to unmask] or visit the website www.prstatistics.com Please feel free to distribute this information anywhere you think suitable Upcoming courses - email for details [log in to unmask] 1. ADVANCED PYTHON FOR BIOLOGISTS (February 2017) #APYB http://www.prstatistics.com/course/advanced-python-biologists-apyb01/ 2. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R (February 2017) #SIMM http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm03/ 3. NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March 2017) #NTWA http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/ 4. ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (April 2017) #MVSP http://www.prstatistics.com/course/advances-in-spatial-analysis-of-multivariate-ecological-data-theory-and-practice-mvsp02/ 5. INTRODUCTION TO STATISTICS AND R FOR BIOLOGISTS (April 2017) #IRFB http://www.prstatistics.com/course/introduction-to-statistics-and-r-for-biologists-irfb02/ 6. ADVANCING IN STATISTICAL MODELLING USING R (April 2017) #ADVR http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr05/ 7. GEOMETRIC MORPHOMETRICS USING R (June 2017) #GMMR http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/ 8. MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (June 2017) #MASE http://www.prstatistics.com/course/multivariate-analysis-of-spatial-ecological-data-using-r-mase01/ 9. TIME SERIES MODELS FOR ECOLOGISTS USING R (JUNE 2017 (#TSME) 10. BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS (July 2017) #BIGB http://www.prstatistics.com/course/bioinformatics-for-geneticists-and-biologists-bigb02/ 11. SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (August 2017) #SPAE http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r-spae05/ 12. ECOLOGICAL NICHE MODELLING (October 2017) #ENMR http://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr01/ 13. INTRODUCTION TO BIOINFORMATICS USING LINUX (October 2017) #IBUL http://www.prstatistics.com/course/introduction-to-bioinformatics-using-linux-ibul02/ 14. STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY BIOLOGISTS (October 2017) #SEMR 15. GENETIC DATA ANALYSIS USING R (October 2017 TBC) #GDAR 16. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (November 2017 TBC) #LNDG http://www.prstatistics.com/course/landscape-genetic-data-analysis-using-r-lndg02/ 17. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (November 2017) #ABME http://www.prstatistics.com/course/applied-bayesian-modelling-ecologists-epidemiologists-abme03/ 18. INTRODUCTION TO METHODS FOR REMOTE SENSING (November 2017) #IRMS 19. INTRODUCTION TO PYTHON FOR BIOLOGISTS (November 2017) #IPYB http://www.prstatistics.com/course/introduction-to-python-for-biologists-ipyb04/ 20. DATA VISUALISATION AND MANIPULATION USING PYTHON (December 2017) #DVMP http://www.prstatistics.com/course/data-visualisation-and-manipulation-using-python-dvmp01/ 21. ADVANCING IN STATISTICAL MODELLING USING R (December 2017) #ADVR http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr07/ 22. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (January 2018) #IBHM http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm02/ 23. PHYLOGENETIC DATA ANALYSIS USING R (TBC) #PHYL 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/