Course information

Course title
3D Geometric Morphometrics
University / Organization
Transmitting Science S. L.
City
Piera
Country
Barcelona
Academic level
Both Msc and PhD
Language
Spain
School
Address
Course director
Course lecturer(s)
Melissa Tallman
Course aim
This course is entitled to teach the main concepts of shape analysis based on three-dimensional landmark coordinates. In this course, you will learn to manipulate 3D models and use them to collect landmark data, take measurements, and to quantify and visualize the main differences in shape.
Course contents / programme
Types of data acquisition. Collecting CT scans & Surface Scans. – Demonstration of Stratovan Checkpoint. Brief Review of Fundamentals of Morphometrics. – How to choose landmarks. – Generalized Procrustes Analysis. – Other types of alignment. – Thin plate spline warping. Processing Microscribe data. – Using DVLR to merge two views. – Using resample to resample a line. Using Landmark Editor to collect data on surfaces. – Sliding semi-landmarks (using R geomorph package). How to do a precision test on 3D data. Data exploration: PCA analyses. – Using Morphologika. – Using MorphoJ. – Between-group PCAs. – PCAs in Procrustes form space. Visualizing shape change. – Using MorphoJ in conjunction with Landmark Editor. – Making calculations and visualizing shape changes in PCA morphospace. – Calculating PCA scores post hoc. Data exploration: Regressions. – Visualizing change that is associated with size (MorphoJ). – Removing change associated from size from your data (MorphoJ). – Common allometric trajectories. – Comparing vector directions. – Extracting linear dimensions from 3D data and using them as covariates. Data exploration: PLS analyses. – Using MorphoJ to mean center (or not). – Visualizing shape change in Landmark editor. Data exploration: Phylogeny. – Visualizing shape changes in MorphoJ along a tree. – Importing covariates and visualizing shape change associated with taxonomy (using MorphoJ). – Creating a phyomorphospace. – Correcting for phylogeny in PCA. Data interpretations: Using mean configurations (PAST) and Procrustes distances. – Minimum spanning trees. – Variability within a sample (comparing fossil distributions to extant distributions). Retrodeformation. Programs that we will use: – Stratovan Checkpoint (temporal licences will be provided during the course). – DVLR (free). – Resample (free). – Landmark Editor (free). – Morphologika (free). – MorphoJ (free). – PAST (free). – R (free, only for sliding semilandmarks, no previous knowledge is required). – Microsoft Excel.
Required Knowledge and preparation
Teaching methods
Assessment
Course type
Summer School
Consecutive days
Yes
Online course
Yes
Duration (net days)
5
Credits
2
Course fee
650 € (520 € Ambassador institutions)
Direct e-mail to register
courses@transmittingscience.org
Paper submission required?
Logo of institution
front approval