Our research aims to understand what drives phenotypic differences among individuals of a population.
Doing that involves a combination of methodology and theoretical developments, and the use of publicly available data and data generated by the team or collaborators that we use for hypothesis testing and statistical modelling.
Humans and animals show an extraordinary range of phenotypic variation. We know that differences among individuals are driven by genetic and environmental factors. Discovery of these factors has been fuelled in later years by technology, co-operation among scientists and big datasets. Our lab has used large human cohorts as a model to explore phenomena like assortative mating, sexual dimorphism, indirect genetic effects, gene by environment interactions or elusive epistatic effects. Furthermore, it has allowed us to perform Genome-Wide Association Studies (GWAS) at an unprecedented scale in terms of cohort size and number of traits, thereby providing a first global insight into pleiotropy. Despite the enormous progress in field of GWAS, these remain computationally intensive, and labour intense. We work on developing tools that are accessible to most users and that will allow capitalising on the genomics revolution.