Esther Robb

The paper introduces Watershed-DL, a framework integrating sequence-to-omics predictions and multi-omics data to prioritize rare variants, finding it increases prioritized variants by 61.4% and identifies candidate disease alleles.

This paper benchmarks 7 TR genotyping tools using Nanopore long-read data, finding that no single tool is best across all metrics, and that sequence-level accuracy is crucial for clinical and population studies.

The paper predicts the regulatory effects of non-coding variants across brain and heart cellular contexts using deep learning, identifying rare variants with significant developmental impacts.

The paper uses long-read sequencing on 100 samples from the 1000 Genomes Project to identify structural variants and improve understanding of human genetic variation.