Lucija Klaric
UKRI Research Fellow
- MRC Human Genetics Unit
- Institute of Genetics and Molecular Medicine
- College of Medicine and Veterinary Medicine
Contact details
Address
- Street
-
MRC Human Genetics Unit
MRC Institute of Genetics & Molecular Medicine
The University of Edinburgh
Western General Hospital
Crewe Road - City
- Edinburgh
- Post code
- EH4 2XU
Background
Lucija earned her PhD in human genetics at the University of Edinburgh, where she studied genetic regulation of protein glycosylation. Working as a research fellow at the University of Edinburgh and data analyst in Genos Ltd on the project “Methods for Integrated Analysis of Multiple Omics datasets”, she gained insights both in bottom-up pre-processing and analyses of glycomics data, but also in integrating these with genomics and clinical data. She has a general interest in data integration of different omics and has been appointed to a UKRI innovation fellowship in data science to work on linking whole genome and exome sequencing data with different omics in the context of complex traits and diseases.
Qualifications
MSc (2012, Molecular Biology, Faculty of Science, University of Zagreb)
PhD (2018, Human Genetics, MRC HGU IGMM, University of Edinburgh)
Undergraduate teaching
Supervisor of the Phenotype Imputation honours project
Current PhD students supervised
Arianna Landini - https://www.ed.ac.uk/profile/arianna-landini
Zhe Huang - https://www.ed.ac.uk/profile/zhe-huang
Current research interests
My main research focus has been genetic regulation of omics traits. I work on associations of phenomics and proteomics and whole genome and exome sequencing data, with a special focus on rare variants.Past research interests
In past I mostly focused on genetic regulation of protein glycosylation, association of glycans with wide variety of health-related traits. As part of the EU FP7 project Methods for Integrated Analysis of Multiple Omics Datasets (MIMOmics) I gained experience in study design and assessing the influence of different data pre-processing approaches on downstream statistical analyses, as well as in integration of glycomics and other omics datasets.Current project grants
UKRI Innovation/Rutherford Fund Fellowship