Dhrithi Deshpande

The paper introduces a machine-learning framework to model disease effect sizes from GWAS data, identifying constrained regulatory variants as key functional components and improving variant prioritization.

This study shows that better software development practices for RNA-seq tools lead to more citations, as evidenced by a strong statistical association between development quality and citation counts.

This study evaluates the reproducibility of eight read alignment tools using synthetic replicates, finding significant variability in their performance and impact on downstream variant calling.