What do we do?
At 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 genome-wide association studies (GWAS) with different -omics data to enhance our understanding of the genetic network of the human genome. We are also very involved in the activities of the GIANT consortium as well as in various clinical genetic analyses.
During 2016, Aurélien Macé and Jing Cui successfully defended their PhD theses, and Sina Rüeger (PhD student) received the Young Investigator Award for the best talk in statistical genetics at the European Society of Human Genetics (ESHG) conference. We developed a new software (PASCAL) for fast and rigorous computation of gene and pathway scores from SNP-based summary statistics. Another tool to reliably call and associate Copy Number Variants (CNVs) was also published. Finally, we participated in major collaborative efforts (published in Nature, Nature Genetics, Nature Communications) to unravel the genetic basis of birth weight, educational attainment, blood pressure and leptin levels.
Main publications 2016
- New quality measure for SNP array based CNV detection. Macé A et al. Bioinformatics. 2016 Nov 1;32(21):3298-3305.
- Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases. Marbach D, Lamparter D, Quon G, Kellis M, Kutalik Z, Bergmann S. Nat Methods. 2016 Apr;13(4):366-70.
- Narcolepsy-Associated HLA Class I Alleles Implicate Cell-Mediated Cytotoxicity. Tafti M et al. Sleep. 2016 Mar 1;39(3):581-7.