Elena P. Sorokin

The paper analyzes rDNA copy number variation in humans, finding distinct associations with metabolic diseases and growth traits.

This paper uses machine learning to impute MRI-derived organ volumes and applies bias-corrected GWAS to identify genetic loci associated with these traits across 450,000 individuals.

The paper identifies a novel risk locus for PAD on 2q35 in Dominicans using admixture mapping and health systems data.

This study links genomic data with EHRs to identify health outcomes enriched in sub-populations, revealing both known and novel associations.

The paper uses deep learning to quantify abdominal organ traits from MRI scans and identifies genetic associations with organ health parameters.

The paper conducts a GWAS in non-European populations, identifies new genetic loci, and highlights the importance of diverse cohorts for understanding complex traits.

The paper analyzes REA data collection practices and disparities in gnomAD, highlighting the need for standardized frameworks to improve diversity and variant interpretation in clinical genomics.

The paper identifies a common collagen disease in Puerto Ricans using identity-by-descent mapping and genomic data from a health system.