Section of Statistical Multi-Omics
The main focus of our research is dissection of the genetic architecture, and multiple omics data layers for complex human and animal characteristics and their relations to symbiotic microbiota. We also develop novel statistical methods for multi-phenotype analysis, CNV detection, sequencing studies and multi-omics data.
We are a research group in the Department of Clinical and Experimental Medicine within the School of Biosciences and Medicine here at Surrey. Our Section is led by Professor Inga Prokopenko and is composed of lecturer in statistical multi-omics, Dr Marika Kaakinen, postdoctoral and visiting fellows, PhD, MSc, and BSc students.
We lead and participate in numerous genome-wide association study efforts within large-scale international consortia, including MAGIC, DIAGRAM, EGG, GIANT, MiBioGen and others.
- Animal genetics, genetic data imputation and comparative GWAS
- CNV detection and analysis in sequencing and genotyping data
- Co-morbidity between type 2 diabetes and cancer/depression/blood pressure
- Genetics of glycaemic and related metabolic traits, type 2 diabetes, metabolites and proteins
- Genetics of Parkinson’s disease
- Genomics of pulmonary arterial hypertension
- Host genetics and gut microbiome
- Human gut microbiome and polycystic ovary syndrome
- Linking genetics to phenotypes from metagenomes
- Machine learning methods for phenotype prediction from longitudinal multi-omics data
- Mendelian randomisation analyses to dissect causal relationships between traits and diseases
- Missing data imputation for high-dimensional omics data
- Multi-phenotype analysis methods for omics data (rare and common genetic variants, methylation data, summary statistics)
- Nutrition and gut health.