What we do
In the Statistical Genetics Group, we are interested in the development of statistical methodologies in order to decipher the genetic architecture of complex human traits related to obesity. To do this, we efficiently combine large-scale genome-wide association studies (GWAS) with various -omics data. Our methods improve genetic fine-mapping, reveal gene-environment interactions, dissect genetic subtypes of obesity, enhance causal effect estimation and detect various statistical artefacts. Furthermore, we are involved in large consortia researching the genetic basis of anthropometric traits (GIANT) and longevity (LifeGen).
Find out more about the Group’s activities
Highlights 2020
- Our group (jointly with Matt Robinson's) organised the European Mathematical Genetics Meeting 2020
- Group member Liza Darrous received the prestigious Lodewijk Sandkuijl Award for the Best Talk in statistical genetics at the yearly conference of the European Society of Human Genetics
Main publications 2020
- Sulc J et al.
Quantification of the overall contribution of gene-environment interaction for obesity-related traits
Nature Communications, 10.1038/s41467-020-15107-0 - Mounier N and Kutalik Z
bGWAS: an R package to perform Bayesian genome wide association studies
Bioinformatics, 10.1093/bioinformatics/btaa549 - Porcu E et al.
Causal Inference Methods to Integrate Omics and Complex Traits
Cold Spring Harb Perspect Med, 10.1101/cshperspect.a040493
