Lindsay A. Guare

TRACE uses a fine-tuned biomedical language model to identify drug-gene pairs from TWAS data, achieving high recovery rates in validation studies.

The PMBB Geno-Pheno Toolkit provides modular pipelines for cross-biobank association analyses, supporting GWAS, ExWAS, and PheWAS with containerized workflows.

DRIVE-KG integrates multi-omics data into a knowledge graph to discover SNP-phenotype associations and predict endometriosis status, uncovering new variant-phenotype links and improving classification performance.

This study performs a genome-wide association study for Long COVID, identifying a significant association with the FOXP4 locus and highlighting the role of pulmonary dysfunction and COVID-19 severity.

The paper examines how genetic and environmental factors, including social determinants of health, influence women's health outcomes by analyzing polygenic risk scores and environmental exposures in the All of Us cohort.

Population-stratified GWAS of 2,068 traits in 635,969 Million Veteran Program participants, 29% genetically non-European, yields 98,485 associations and 57,601 fine-mapped signals with largely shared cross-population architecture.

This study identifies ancestry-specific and sex-specific genetic loci for primary open-angle glaucoma through a meta-analysis of 15 biobanks, highlighting shared biology with vascular mechanisms and cell proliferation.

This paper introduces EDGE, a method to detect nonadditive genetic effects in GWAS, finding nonadditive patterns in over 52% of significant loci for coronary artery disease and body mass index.

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 an NLP-ML approach to annotate -omics samples with tissue and cell-type labels using free-text metadata, outperforming existing methods and demonstrating biological relevance.