Snehal B. Patil

This paper develops a machine learning classifier to subtype HPV+ HNSCC tumors into IMU or KRT using bulk RNA-seq data and validates its accuracy across multiple cohorts.

The Michigan Genomics Initiative links genotypes with electronic clinical records in Michigan Medicine patients, showing higher disease prevalence and validating GWAS findings.

This study evaluates polygenic risk score methods across diverse biobanks and ancestries, finding that European reference panels often yield better performance, while PRS-CS outperforms P+T for high-heritability traits.

This paper shows that meta-analysis fine-mapping is often miscalibrated due to cohort heterogeneity and introduces a QC method to identify suspicious loci.

Meta-analysis of harmonized GWAS from up to 18 biobanks (six ancestry groups) across 14 endpoints replicated 320 known loci and identified 188 apparently novel loci.

The paper develops ExPRSweb, an online repository of polygenic risk scores for common exposures, showing improved prediction of chronic conditions when combined with traditional PRSs.

This study identifies 17 genetic risk loci for spontaneous coronary artery dissection (SCAD), including 12 new ones, and highlights genes related to artery integrity and coagulation.

This study identifies 424 new loci associated with kidney function using GWAS data from over 1.2 million individuals and prioritizes 34 genes for further functional investigation.

The paper develops genome-wide enhancer-to-target gene assignments across >500 cell types and shows they outperform naive methods in gene set enrichment analysis.

The paper introduces Cancer-PRSweb, an online repository of polygenic risk scores for cancer traits, evaluated in two biobanks with predictive performance metrics and phenome-wide association studies.

Poly-Enrich improves gene set enrichment testing for genomic regions by modeling peak counts with a negative binomial model, outperforming previous methods in certain scenarios.