Sayan Ghosal

VariantFormer predicts gene expression from diploid genomes, outperforming existing models and improving eQTL effect size estimation across ancestries and tissues.

BEATRICE identifies causal variants from GWAS summary data using a Bayesian framework, outperforming baselines in coverage and finding the APOEε2 allele in Alzheimer's disease.

This paper introduces a graph convolutional network that links genetic risk pathways with neuroimaging phenotypes in schizophrenia, achieving better classification performance than existing methods.