Project title
Identifying novel, conditional and joint genetic effects on Parkinson’s disease risk
Supervisory Team
Principal Supervisor: Professor Dale Nyholt
Associate Supervisor: Associate Professor Divya Mehta
Project description
Linduni’s MPhil project aims to analyse existing ExomeChip-based genome-wide association data to demonstrate the utility of genotype imputation with whole genome sequence-based haplotype reference panels, and recently developed statistical and machine learning approaches to identify novel common and rare genetic variants and their interactions associated with Parkinson’s disease risk.
Short biography
Linduni has a keen interest in variable selection methods for high-dimensional data analysis, with particular application to -omics data. She recently finished her MPhil degree from Statistical Genomics and Epidemiology Lab, QUT. Prior to her MPhil, she worked as a Lecturer and Research Assistant in Sri Lanka where she worked on developing a feature selection method for increasing the classification accuracy of spontaneous preterm delivery predictor in asymptomatic women. She completed her B.Sc. in Statistics from University of Sri Jayewardenepura, Sri Lanka with a focus on survival analysis techniques.
Education
2016 Bachelor of Science in Statistics from the University of Sri Jayewardenepura, Sri Lanka