Christopher Toh

This paper develops a genetic risk score for ovarian cancer using chromosomal-scale length variation, showing it can stratify risk with high accuracy.

The paper evaluates a genetic risk score based on chromosome-scale length variation and machine learning to predict severe COVID-19 outcomes, finding limited clinical utility.

This paper shows that chromosomal-scale length variation in germline DNA can predict cancer risk better than SNP-based methods in two datasets.