Stephen Rong

Identifying non-coding variant effects at scale via machine learning models of cis-regulatory reporter assays

This study introduces MPAC, a machine learning model that predicts the cis-regulatory impact of non-coding variants, demonstrating its accuracy across diverse applications and datasets.

One-Size-Fits-Many: Antisense oligonucleotides for rescuing splicing mutations in hotspot exons

The paper identifies splice-disrupting mutations in hotspot exons and shows that antisense oligonucleotides (ASOs) can revert splicing defects in these exons.

Large scale functional screen identifies genetic variants with splicing effects in modern and archaic humans

The paper identifies splicing variants in modern and archaic humans using functional assays and shows differences in purifying selection and adaptive introgression.