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    Header of Geometric Morphometrics at Transmitting Science

Course – 7th Edition

Geometric Morphometrics in R

January 20th-24th, 2020, Barcelona (Spain)

Geometric Morphometrics_transparente

Geometric Morphometrics

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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).

Contact

courses@transmittingscience.com

LOCATION

Can Carol

C/ Font de la Reina, 5
08786 Capellades, Barcelona (Spain)

How to get there

DATE

January 20th-24th, 2020

LANGUAGE

English

COURSE LENGTH & ECTS

40 hours on-site.

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.

PLACES

Places are limited to 22 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

MONDAY

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.

TUESDAY

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.

WEDNESDAY

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. Outlines.

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.

THURSDAY

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.

FRIDAY

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

Schedule

Course Schedule

Participants will make their own way

  • Monday to Friday:
    • 9:30 to 13:30 Lessons.
    • 13:30 to 15:00 Lunch (included).
    • 15:00 to 19:00 Lessons.

The class schedule is approximate; it is possible that the content of one day may run into the next and a working day may be longer than advertised.

Course + Accommodation Package Schedule
  • Sunday:
    • 19:00 Meeting point in Plaza Catalunya (Barcelona) to take the bus to Capellades. If you are planning to arrive later, you can find more information on how to get there.
    • 20:00 Registration in the Hostel.
    • 20:30 Dinner.
  • Monday to Thursday:
    • 08:00 to 09:00 Breakfast
    • 9:30 to 13:30 Lessons
    • 13:30 to 15:00 Lunch (included)
    • 15:00 to 18:00 Lessons
    • 20:00 Dinner
  • Friday:
    • 8:00 to 9:00 Breakfast.
    • 9:30 to 13:30 Lessons
    • 13:30 to 15:00 Lunch (included)
    • 15:00 to 18:30 Lessons
    • 19:00 Meeting point in the Hostel to take the bus to Barcelona city.
    • 20:30 Arrival at Plaza Catalunya (Barcelona).

The class schedule is approximate; it is possible that the content of one day may run into the next and a working day may be longer than advertised.

Accommodation

If you choose the Accommodation Package you will be hosted at Rural House Can Carol, in shared en-suite rooms, although you will only share rooms with other course participants (male or female only).

If you prefer to stay in a single en-suite room, you can do so with a supplementary charge.

The Accommodation Package includes transportation from the centre of Barcelona city to the venue and back, at the start and end of the course, respectively. The trip takes around 1 hour each way. 

If the number of participants exceeds the available rooms at Can Carol, some of them could be accommodated in the Hotel Tall del Conill, by registration order. The hotel is at 10 minutes walking, although transport will be provided in the morning and after dinner. Lunches and dinners will be with the whole group.

Accommodation is included from Sunday (check-in) to Friday (check-out). Breakfast, lunch and dinner are also provided during the week, starting from the dinner of Sunday to lunch of Friday (included).

Other accommodation options

If you do not want the Accommodation Package, accommodation is available in places other than Can Carol: Where to stay near the Venue.

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.

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