In this five-day course we will introduce the main concepts that underlie many of the models that are frequently used in population genetics. We will focus on the importance of demographic history (e.g. effective sizes and migration patterns) in shaping genetic data. We will go through the basic notions that are central to population genetics, insisting particularly on the statistics used to measure genetic diversity and population differentiation. The course will also cover a short introduction to coalescent theory, Bayesian inference in population genetics and data simulation. We will also introduce methods that have been recently developed to analyse genomic data such as the PSMC method of Li and Durbin that reconstructs the demographic history of a species or population with the genome of a single individual.

IGC is organizing a workshop with speakers from R&I Institutions to share showcases, a group simulation of a data management plan and tools available to improve your skills.

In this course, we will explore the use of modern bioinformatic tools that allow researchers to use pangenomes as their reference system when engaging in studies of organisms of all types. Such techniques will aid any researcher working on organisms of high genetic diversity or on organisms lacking a high-quality reference genome. This course targets all researchers interested in learning about an exciting paradigm shift in computational genomics.

This training course is aimed at researchers who are not expert in proteomics and want to integrate quantitative proteomics results into wider biomedical experiments. We will focus on quality control from an end-user perspective, link to the underlying genomic context, multivariate analysis, protein complexes investigation, and compare different platforms for biological interpretation.

Metagenomics is a branch that processes large quantities of biological data, extracted directly from an environment. In order to derive useful information from this great volume of data, it is necessary to make use of informatics support, which, in turn, implies to a need to know how to use various tools and programming languages, and the need to develop tools to simplify the data analysis. Biome-Shiny is a tool created to bridge the gap between traditional Biology and Bioinformatics, providing a user-friendly interface to visualize microbiome data, allowing any user to generate and export interactive plots and tables, without needing to understand the background code.

This intermediate level course is one of our Foundations courses. It covers essential statistical concepts and methods for extracting insights from empirical data in the life sciences. The course positions applied statistics, starting from important aspects of experimental design and data exploration. We then move into statistical modeling and data analysis. We will focus on the link between linear regression and analysis of variance. Together, these methods contribute to the study of General Linear Models. The course also introduces the basics of non-parametric testing, and addresses categorical data analysis and logistic regression.

BioData.pt Crash Course: Microbiome Visualization with Biome-Shiny is an introductory one-day workshop seeking to provide users with the knowledge to create, analyze and visualize microbiome data.