Solve shape-analysis problems in R using measurements, landmarks and outlines. The programme develops data organisation and image processing before geometric transformations, alternative superimposition methods and Procrustes analysis. Participants visualise shape differences, test allometry and multivariate hypotheses, and compare principal-component, discriminant and regression approaches. Outline analysis introduces several Fourier representations and their statistical interpretation; participants can bring their own morphological datasets. Live sessions: 10, 11, 14, 15, 16, 17 and 18 Dece
In Applied Mathematics and Biology
Quantify biological shape variation and its covariation with the physical environment through geometric morphometrics. This introductory workshop develops landmark and semilandmark configurations, data acquisition and digitisation, Generalized Procrustes Analysis and shape space. Participants compare alternative alignment methods, visualise thin-plate-spline deformations in two and three dimensions, and use principal components, multivariate regression and allometry to interpret variation. Practical work uses TPS software and MorphoJ, with emphasis on interpreting biological questions through
Learn to quantify and interpret biological form using two- and three-dimensional geometric morphometrics. Lectures and practical sessions cover landmark, semilandmark, outline and surface data, digitisation methods, study design and data-quality checks. Generalized Procrustes Analysis provides the foundation for principal components, group comparisons, linear models and allometry. Further sessions address symmetric structures and the possibilities and limitations of machine-assisted data acquisition. Participants assemble a basic analysis workflow and can discuss their own datasets. Teaching e