• Advanced Courses in Life Sciences

    Header of Evolution at Transmitting Science

Live Online Course – 3rd Edition

Modelling and Analysing Multivariate Trait Evolution using mvMORPH

May 15th-26th, 2023

Live sessions will be recorded

Course Modelling and Analysing Multivariate Traits Evolution on Phylogenetic Trees using mvMorph

Course overview & Programme

In this course, participants will be introduced to multivariate phylogenetic comparative methods with the mvMORPH R package.

The mvMORPH package contains tools for modelling the evolution of correlated continuous traits (e.g. morphometric measurement, geometric morphometric datasets, life history traits, gene expression data, etc.) on phylogenetic trees [with either fossil species, extant species or both] as well as statistical tools such as multivariate generalized least squares (GLS) linear models -e.g. multivariate regressionMANOVAMANCOVA – for studying comparative datasets.

During the course, participants will first be introduced to some theory with illustrative examples (both from simulated data as well as students’ own datasets) and will then learn how to interpret the models, their parameters, as well as how to assess their reliability.

We would like to encourage participants to bring along their own dataset with a matching phylogenetic tree (or sample of trees) to analyse between the live sessions and discuss with the instructor.

  • Introduction to phylogenies, trait evolution and the comparative methods
    • Short introduction on the modelling rationale and theoretical basis on trait (multivariate) evolution and models
    • Illustration with simulation examples in R (e.g. 3D plot of bivariate processes)
  • Modelling the evolution of traits on trees (simulations, model fit and comparison)
    • Review of some multivariate models (BM, OU, EB, Shift…), assumptions, and limits.
    • Step by step procedure for model comparison and interpretation of parameters using simulated and empirical datasets.
    • Hypothesis testing and constrained parameters estimation
  • Working with high-dimensional datasets
    • Introduction to the high-dimensional challenges (when the number of traits approach or is larger than the number of species such as in geometric morphometric and gene expression data) of comparative methods (e.g. comparison of likelihood, penalized likelihood, and alternative techniques)
    • Model fit on high-dimensional datasets (model comparison, estimation of parameters, reconstruction of evolutionary trajectories)
  • Fitting linear models (MANOVA, MANCOVA, multivariate regression) to comparative data
    • Introduction to phylogenetic linear models and multivariate counterparts, their assumptions, the various tests.
    • Linear hypothesis testing
    • Illustration on both empirical and simulated datasets
  • Using diagnostic plots, simulations, and Monte-Carlo techniques to assess the reliability of model fit and parameters
    • Introduction to bootstrap and parametric bootstrap techniques, estimation of uncertainties, assessing relative and absolute fit to the data.
  • Imputing missing values and estimating ancestral states
    • Introduction on how to estimate missing values and ancestral states; formatting the data, etc.
  • Inferring dependencies and causal links between traits evolving on trees
    • Introduction to inferring graphs of dependencies between evolving traits (e.g. partial correlations, graphical LASSO, etc.)
    • Using multivariate models to infer “causal” links (e.g, comparative study on sexual dimorphism)
  • Working on non-ultrametric trees (e.g., fossil data, virus strains)
    • Introduction on identifiability issues and the strength and weaknesses of working with non-ultrametric trees
    • Illustration with worked examples [and students’ datasets]
  • Transformations and data pre-treatments
    • Discussions on the use of pre-transformations (eg log-transformation) and data reduction techniques (PCA, phylogenetic PCA) in comparative datasets; measurement error and intraspecific variance.
  • (Digression) Modelling multivariate time series
    • Illustration on how to model multivariate traits on time-series rather than phylogenetic trees in mvMORPH (inferring trends, causal links, etc.)
  • Summary
    • Summary on the various techniques’ strengths and weaknesses, model assumptions, and alternative tools currently available on R with some worked examples.

Graduate or postgraduate degree in Biomedical, Life or Earth Sciences. This course is not introductory: knowledge of multivariate statistics and R at user level is need it to follow the course. Familiarity with univariate phylogenetic comparative methods is highly recommended.

Participants must have a personal computer (Windows, Mac, Linux). The use of a webcam and headphones is strongly recommended, and a good internet connection.

Although not a requirement, participants are encouraged to bring along their own dataset with a matching phylogenetic tree (or sample of trees).

Instructor

Julien Clavel instructor for Transmitting Science

Dr. Julien Clavel
CNRS
France

Dates & Schedule

May 15th-26th, 2023

14:00-19:00 (Madrid time zone)

Online live sessions on May 15th, 17th, 22nd, 24th, and 26th; 14:00 to 16:30 and 17:00 to 19:00 (Madrid time zone).

The rest of the time will be taught with assignments, to be done between the live sessions.

Total course hours: 30

22.5 hours of online live lessons, plus 7.5 hours of  participants working on their own, with tutored exercises

This course is equivalent to 1 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.

Haris Saslis coordinator for Transmitting Science

Dr. Haris Saslis
Transmitting Science
Greece

Soledad De Esteban-Trivigno Transmitting Science coordinator

Dr. Soledad De Esteban-Trivigno
Transmitting Science
Spain

Fees & Discounts

  • Course Fee
  • Early bird (until February 28th, 2023):
  • 486 €
    (388.80 € for Ambassador Institutions)
  • Regular (after February 28th, 2023):
  • 650 €
    (520 € 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.

Registration

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