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AC AdvancedR 2025/2026

Objectives

Provide students with statistical knowledge and tools to manipulate, analyse and visualise biological data with R. Introduction to modelling, simulations and Bayesian statistics.

Throughout the course, students will be encouraged to apply the knowledge obtained to data from their own work. Depending on the interests of the participants, some of the content can be adjusted to focus more on examples from evolutionary biology or ecology. On the last day, each student will do a small presentation with data available from their own work or possible applications to their research question.

Topics

  • Refresher into R
  • Exploratory analysis for ecology and evolution (Principal Component Analysis)
  • Linear regression and ANOVA
  • Hypothesis testing using bootstrap and permutations
  • Introduction to analysis of population genetics in R
  • Modelling and simulation of dynamic systems
  • Bayesian statistics and advanced inference algorithms (Markov chain Monte Carlo)
  • Students case studies

Participants must be present at 85% of the contact hours (meaning they can miss one half-day) and actively participate in all activities.

This course can give credits to PhD programmes at CIÊNCIAS or programmes with partnership from CIÊNCIAS and other institutions with 6h-7h of contact hours per ECT, as a function of specific requirements. For these students, in addition to the exercises done during the week, delivering a written report after the course is mandatory. For programmes with fewer hours of contact per ECT (6h/ECT, getting 6 ECTs from the course), students must do an additional assignment (summary report). If needed, 1 or 2 additional hours of contact may be added. Such report(s) are also advised for other students requesting accreditation of the course in their institutions.

Minimum requirements: Knowledge of R programming syntax and Rstudio. Preference will be given to participants who attend the R introductory course or who have previous knowledge of R.

Directed to: PhD or MSc students in Biology, Evolution, Ecology or related areas, and postdocs and other professionals working on related topics.

Detailed plan

  • Refresher into R. A very quick refresher on R language to be sure that all students know basic R programming.
  • Exploratory analysis for ecology and evolution (Principal Component Analysis). The students will learn how to perform and interpret the results of Principal Component Analyses (PCA) and Multivariate Evolutionary Analyses.
  • Linear regression and ANOVA (factorial and nested ANOVA). Students will learn how to perform and interpret results from general linear models.
  • Hypotheses testing using resampling approaches (e.g. bootstrap and jackknife). Many datasets in ecology and evolution violate assumptions of classical statistical tests, and hence resampling approaches became common practice. Students will learn how to perform hypothesis testing using permutation tests, bootstrap and jackknife.
  • Introduction to analysis of population genetics in R. The students will learn how to compute basic genetic statistics (genetic diversity, FST), test Hardy-Weinberg equilibrium, compare genetic diversity between populations and perform PCA with genomic data.
  • Modelling and simulation of dynamics systems. We will use examples from population genetics (genetic drift) and population dynamics (Lotka-Volterra predator-prey model) to illustrate how R can be used to perform simulations. The students will learn how to model and perform simulations of populations evolving through time.
  • Introduction to Bayesian statistics. The students will learn how to use a Markov chain Monte Carlo (MCMC) algorithm to estimate parameters of different models of population dynamics.
  • Student’s case studies.

Fees

Free for 1st year PhD students in Doctoral programmes at CIÊNCIAS (e.g. Biology), Biodiversity, Genetics and Evolution (BIODIV ULisboa; UPorto), Biology and Ecology of Global Changes (BEAG ULisboa, UAveiro) and Sustainability Science (ULisboa, several institutions), when the course counts credits for their formation, in which case the delivery of a final report done after the course is mandatory; the course is also free for more advanced PhD students of the BIODIV programme (ULisboa or UPorto); 50 € for more advanced PhD students of CE3C; 80 € for PhD students of the PEERS network (CFE); 125 € for CIÊNCIAS Master students and unemployed; 180 € for BTI, BI and other PhD students*; 250 € for professionals and postdocs.

(* For PhD students also doing the Introduction to R course, the fee is reduced to 120 €)

When the maximum number of students is reached, 10 vacancies will be available for non-paying 1st year PhD students mentioned above, being, by order of preference, students from: 1) CE3C; 2) BIODIV (not from CE3C); 3) CIÊNCIAS (not from CE3C); 4) Sustainability Science (not from CE3C or CIÊNCIAS); 5) BEAG (not from CE3C or CIÊNCIAS).

How to Apply

Candidates should complete the APPLICATION FORM, which will be available in this section when the call is open.

Please note that this is a shared application form for both the Introduction to R and the Advanced R courses. Be sure to clearly indicate whether you are applying to one or both courses in the relevant field. If you wish to attend both, submit only a single application form.

The form is strictly confidential, as explained in its introduction, and the data are required because the CE3C Advanced Courses are also offered as part of the PRR programme of CIÊNCIAS.

When filling out the form, mind to:

  • FILL ALL THE MANDATORY FIELDS;
  • UPLOAD CV AND MOTIVATION LETTER, both mandatory; use the names as instructed;
  • If you want to resume later, SAVE the form; otherwise, you will need to fill everything out again;
  • At the end, SUBMIT the form before exiting.


If you have any questions, please contact the coordinator of the CE3C Advanced Courses, Margarida Matos (mmmatos@fc.ul.pt), and the teacher, Inês Fragata (irfragata@fc.ul.pt).

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