Welcome to the website of the Statistical Genetics Group! We are interested in the development of statistical methodologies in order to decipher the genetic architecture of complex human traits. Although our main focus is Genome-Wide Association Studies, we devise integrative analysis tools for different omics data to enhance our understanding of the genetic network of the human genome.

Projects & Collaborators

  1. Genetic fine-mapping:
    1. Quantification of multiple genetic effects at a single locus (G. Ehret, C. Hoggart)
    2. Detecting imperfect tagging (S. Rueger)
    3. Copy number variant associations (A. Mace, A. Reymond, B. Draganski, S. Jacquemont, J. Beckmann)
    4. Exome sequence analysis (I. Xenarios)
  2. Obesity genetics
    1. Age- and gender-dependent genetic factors (R. Loos, T. Winkler, I. Heid)
    2. Dissecting diet and obesity genetics
    3. Index Event Bias (T. Frayling)
    4. Revealing genetic effects that depend on the parental origin of the alleles (A. McDaid, C. Hoggart)
  3. Genetic underpinnings of aging (A. McDaid, MR Rechavi, B Deplancke, J Auwerx)
  4. Integration of intermediate markers to gene-disease associations (R. Rueedi, S. Bergmann)
  5. Genetics of infectious- and autoimmune diseases (P-Y. Bochud, J. Fellay, A. Telenti, M. Tafti)
  6. Mendelian randomization (V. Rousson, M. Bochud)

Furthermore, we are heavily involved in…

…the activities of the GIANT consortium (http://www.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium)

  • sex- and age-specific genetic associations
  • development of quality control methods
  • exome-chip analysis

…various genetic analyses of

  • the Cohorte Lausannoise (CoLaus) study
  • the Swiss Hepatitis C Cohort Study (SCCS)
  • the Swiss Transplant Cohort Study (STCS)
  • the European Narcolepsy Network (ENN)
  • the Hypergenes study