• Advanced Courses in Life Sciences

    Header of Geometric Morphometrics at Transmitting Science

Live Online Course – 10th Edition

Geometric Morphometrics in R

May 2nd-10th, 2024

Live sessions will be recorded

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Course Overview & Programme

Concepts in geometric morphometrics will be taught using a series of original data sets and working in R for solving a series of tasks. The course will start with an introduction to R and will rapidly go into shape analysis with measurements, landmark data and outlines. The participants are welcome to bring their own data and problems so that we may find R solutions.

This is not an introductory course to Geometric Morphometrics, therefore basic knowledge of Multivariate StatisticsR and Geometric Morphometric is recommended in order to take this course.

1. An Introduction to R / Image Processing / Organizing Morphometric Data.

1.1. Some Basics in R.

1.1.1. The R Environment.

1.1.2. R objects, Assigning, Indexing.

1.1.3. Generating Data in R.

1.1.4. 2D and 3D Plots in R; Interacting with the Graphs.

1.2. Organizing Data for Morphometrics.

1.2.1. Data-frame, Array and List.

1.2.2. Converting and Coercing Objects.

1.2.3. Read and Write Morphometric Data in R.

1.3. Image Processing in R.

1.3.1. Reading Various Image Files.

1.3.2. Obtaining Image Properties.

1.3.3. Modifying Image Properties: Contrast, Channels, Saturation Directly from R or by Interfacing R with Imagemagick.

1.4. Simple Tests, Simple Linear Modelling, Alternatives to Linear Modelling, an example using traditional morphometrics.

1.4.1. Defining size and shape using PCA and log-shape ratio approaches.

1.4.2. Getting stats and test outputs.

1.4.3. Testing assumptions of linear modelling.

1.4.4. Testing for allometry and isometry.

1.4.5. Solutions when assumptions of linear modelling are not met.

2. Landmark data.

2.1. Acquiring Landmark Data in R.

2.2. Plotting Landmark Configurations in 2 and in 3D.

2.2.1. Using Different Symbols and Setting the Graphical Parameters.

2.2.2. Labeling Landmarks.

2.3. Geometric Transformation with Landmark Configurations.

2.3.1. Translation.

2.3.2. Scaling using Baseline or Centroid Size.

2.3.3. Rotation.

2.4. Superimposing and Comparing Two Shapes.

2.4.1. Baseline Superimposition.

2.4.2. Ordinary Least Squares Superimposition.

2.4.3. Resistant Fit.

2.5. Representing Shape Differences.

2.5.1. Plotting Superimposed Shape with Wireframe.

2.5.2. Lollipop Diagrams and Vector Fields.

2.5.3. Thin Plate Splines and Warped Shapes.

2.6. Superimposing More Than Two Shapes.

2.6.1. Baseline Registration.

2.6.2. Full Generalized Procrustes Analysis.

2.6.3. Partial Generalized Procrustes Analysis.

2.6.4. Dimensionality of Superimposed Coordinates.

2.7. Exploring Shape Variation and Testing Hypotheses.

2.7.1. PCA.

2.7.2. Multivariate Linear Modelling (Multivariate Regression and         MANOVA).

2.7.3. Allometry free approaches (Burnaby correction).

2.7.4. Linear discriminant and Canonical Analysis.

3. Outline Data.

3.1. Acquiring outline Data in R.

3.2. Fourier Analysis.

3.2.1. Principles.

3.2.2. Fourier Analysis of the Tangent Angle.

3.2.3. Radius Fourier Analysis.

3.2.4. Elliptic Fourier Analysis.

3.2.5. Reduction of Shape Variables.

3.2.6. Statistical Analysis of Shape Variation with Fourier Analysis.

       3.2.6.1. Exploring Shape Variation and Testing Hypotheses.

3.2.6.2. PCA.

3.2.6.3. Multivariate Linear Modelling (Multivariate Regression and MANOVA).

3.2.6.4. Canonical Analysis.

3.3. Combining Landmarks and Curves.

3.3.1. Hybrid Methods between Fourier and Procrustes Analysis.

3.3.2. Sliding Semi Landmarks.

3.4. Solutions for Open Curves.

4. Specific Applications.

4.1. Testing Measurement Error.

4.2. Partitional Clustering.

4.2.1. K-means, Partition Around Medoids.

4.2.2. Mclust.

4.2.3. Combining Genetic, Geographic and Morphometric Data.

4.3. Modularity / Integration Studies.

4.3.1. Two-block Partial Least Squares.

4.3.2. Testing Among Various Sets of Modules.

4.4.Fluctuating Asymmetry and Directional Asymmetry.

4.4.1. Inter-Individual and Intra-Individual Variation.

4.4.2. Object and Matching Symmetry.

4.5.Bending Energy, Uniform and Non-uniform Shape Variation.

Graduate or postgraduate degree in any Life Sciences discipline.

Knowledge of Multivariate Statistics, R and Geometric Morphometrics. Participants that are not familiar with the R environment are strongly recommended to read the book R for beginners and practice before the course, or to take the course Introduction to R. Participants who are not familiar with Geometric Morphometrics are recommended to take first the course Introduction to Geometric Morphometrics.

All participants must bring their own personal laptop (Windows, Macintosh, Linux). A good internet connection is required to follow the course.

Morphometrics with R“, Julien Claude. R. Gentleman, K. Hornik and G. Parmigiani, eds.

Julien Claude instructor for Transmitting Science

Dr. Julien Claude
Institut des Sciences de l’Évolution de Montpellier
France

Testimonials for this course

Geometric Morphometrics in R (onsite) – 3rd edition.

“The course was excellent. The week spent under the guidance of Dr. Julien Claude crystal cleared the concepts of using R in GM. The location and ambience of the course was ideal for such engaging studies. There were participants from diverse field of studies and the best part of the course was that there was ample time to work with our own data and deal with its problems. Dr. Claude always encouraged us to ask questions and was happy to help with our doubts. The course was very well organised, well managed and the food was fantastic!! It is really a course worth to be taken!!!”

Geometric Morphometrics in R (onsite) -4th edition.

“I loved that this course really worked directly with R and had lots of good scripts and example code to work with. Thank you for your efforts in organizing this.”

Geometric Morphometrics in R (onsite) – 6th edition.

“Congratulations, the course was an excellent combination of a great teacher, a very nice human group and delicious coffee breaks. I learned a lot!”

Dates & Schedule

Online live sessions on 2nd, 3rd, 6th, 7th, 8th, 9th, and 10th of May

12:00-17:00 (Madrid time zone)

Total course hours: 40

35 hours of online live lessons, plus 5 hours of participants working on their own.

This course is equivalent to 2 ECTS (European Credit Transfer System) at the Life Science Zurich Graduate School.

The recognition of ECTS by other institutions depends on each university or school.

Language

English

This course will be delivered live online

This course will be taught using a combination of live (synchronous) sessions on Zoom and tasks to be completed in between live sessions on the Slack platform.

Live sessions will be recorded. Recordings will be made available to participants for a limited period of time. However, attendance to the live sessions is required.

Places

Places are limited to 16 participants and will be occupied by strict registration order.

Participants who have completed the course will receive a certificate at the end.

Fees & Discounts

  • Course Fee
  • Early bird (until March 31st, 2024):
  • 495 €
    (396 € for Ambassador Institutions)
  • Regular (after March 31st, 2024):
  • 565 €
    (452 € for Ambassador Institutions)
  • Prices include VAT.
    After registration, you will receive confirmation of your acceptance on the course.
    Payment is not required during registration.

We offer discounts on the Course Fee.

Discounts are not cumulative. Participants receive the highest appropriate discount.

We also offer the possibility of paying in two instalments. Please contact us to request this.

Former participants of Transmitting Science courses receive a 5% discount on the Course Fee.

20% discount on the Course Fee is offered to members of certain organisations (Ambassador Institutions). If you wish to apply for this discount, please indicate it in the Registration form (proof will be asked later). If you would like your institution to become a Transmitting Science Ambassador Institution, please contact us at communication@transmittingscience.com

Unemployed scientists, as well as PhD students without any grant or scholarship to develop their PhD, can benefit from a 40% discount on the Course Fee. This applies only to participants based in Spain. If you wish to ask for this discount, please contact us. The discount may apply for a maximum of 2 places, which will be covered by strict registration order.