• Advanced Courses in Life Sciences

    Header of Geometric Morphometrics at Transmitting Science

Online Course – 8th Edition

Geometric Morphometrics in R

January 18th-26th, 2021

This course will be delivered live online

35 hours of online live lessons,  plus 5 hours of participants working on their own. Online live sessions from 13:00 to 18:00 (GMT+1, Madrid time zone).

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!”

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Geometric Morphometrics in R - ArgentinaCourse Overview

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.

REQUIREMENTS

Graduate or postgraduate degree in any Life Sciences discipline.

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

Contact

courses@transmittingscience.com

Dates

January 18th-26th, 2021

Schedule and Course length

Online live sessions from Monday, January 18th to Tuesday, January 26th, 2021; 13:00 to 18:00 (GMT+1, Madrid time zone).

40 hours.

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

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 of it.

Julien Claude instructor for Transmitting Science

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

Program

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.

Literature

Fees

  • Course Fee
  • Early bird (until November 30th, 2020):
  • 495 € *
    (396 € for Ambassador Institutions)
  • Regular (after November 30th, 2020):
  • 548 € *
    (438.40 € for Ambassador Institutions)
  • This includes course material, coffee breaks and lunches (VAT included).
    * Participants from companies/industry will have an extra charge of 100 €.

You can check the list of Ambassador Institutions. If you want your institution to become a Transmitting Science Ambassador please contact us at communication@transmittingscience.com

Funding

Discounts are not cumulative and apply only on the Course Fee. We offer the possibility of paying in two instalments (contact courses@transmittingscience.com).

Former participants will have a 5 % discount on the Course Fee.

20 % discount on the Course Fee is offered for members of some organizations (Ambassador Institutions). If you want to apply to this discount please indicate it in the Registration form (proof will be asked later).

Unemployed scientists living in the country were the course will be held, as well as PhD students based in that country without any grant or scholarship to develop their PhD, could benefit from a 40 % discount on the Course Fee. If you want to ask for this discount, please contact the course coordinator. That would apply for a maximum of 2 places and they will be covered by strict inscription order.

Registration

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