Utility of in silico prediction tools to aid variant interpretation

Accurate variant interpretation represents is essential for the successful implementation of genetic testing in the clinical setting. Large-scale population-based sequencing projects have provided unprecedented insight into great spectrum of rare coding variation that occurs within the background population. Differentiating genuine disease associated pathogenic variants from rare neutral variants remains a major barrier to the wider implementation of genetic testing (i.e. population-level testing). Recently developed in silico computational prediction tools, which utilise a variety of DNA sequence (e.g. evolutionary conservation) and/or protein structural information for learning aim to address this challenge. However, the utility of these tolls in the clinical and disease-specific areas have not been widely evaluated.

This project will apply a variety of methods to assess whether these novel computational approaches can variant interpretation in the clinical genetic testing workflow. The student should have a background and interest in relevant areas (e.g. genetics, molecular biology, bioinformatics).

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