Stephanie M. Gogarten

Large language model-based bibliometric evaluation of population descriptors in human genetics

This study evaluates adherence to NASEM recommendations on population descriptors in GWAS papers using a large language model-based toolkit, finding improvements over time but limited impact post-report publication.

Building an Interoperable Rare Disease Multi-omic Resource: The GREGoR Data Model and Dataset

The paper introduces a data model and dataset for rare disease research, enabling interoperable multi-omic data integration across clinical sites.

Admix-kit: An Integrated Toolkit and Pipeline for Genetic Analyses of Admixed Populations

Admix-kit provides tools for genetic analysis of admixed populations, enabling simulation, association testing, and polygenic scoring.

Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium

The paper analyzes inflammation biomarkers using whole-genome sequencing from the TOPMed consortium, identifying both single-variant and rare variant associations with inflammatory traits.

Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits - the Hispanic/Latino Anthropometry Consortium

This study identifies novel genetic loci for BMI, height, and WHRadjBMI in Hispanic/Latino populations and shows the benefits of ancestral diversity in GWAS.

Genome-wide association study of body fat distribution traits in Hispanics/Latinos from the HCHS/SOL Study

This study identifies genetic variants associated with body fat distribution traits in Hispanics/Latinos and finds ancestry-specific associations.

BinomiRare: A carriers-only test for association of rare genetic variants with a binary outcome for mixed models and any case-control proportion

The paper introduces BinomiRare, a test for rare variant association with binary outcomes in mixed models, showing it controls type 1 error in simulations and applies it to study genetic variants in disease traits.

Identification of putative causal loci in whole-genome sequencing data via knockoff statistics

This paper introduces a statistical method using knockoff statistics to identify causal loci in whole-genome sequencing data, showing increased discovery potential in Alzheimer's and COPD studies.

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Over 400 million variants, 97% below 1% frequency, emerge from deep whole-genome sequencing of 53,831 diverse TOPMed participants; TOPMed haplotypes enable imputation down to ~0.01% frequency.

Novel genetic determinants of telomere length from a trans-ethnic analysis of 109,122 whole genome sequences in TOPMed

This study identifies 59 sentinel variants and two novel genes associated with telomere length using whole genome sequences from 109,122 trans-ethnic individuals.

Population Stratification at the Phenotypic Variance level and Implication for the Analysis of Whole Genome Sequencing Data from Multiple Studies

The paper addresses variance stratification in pooled whole genome sequencing data, showing how study-specific phenotypic variances affect analysis and introducing a method to improve statistical power and reduce false positives.

Inherited Causes of Clonal Hematopoiesis of Indeterminate Potential in TOPMed Whole Genomes

The paper identifies germline genetic variants associated with clonal hematopoiesis of indeterminate potential (CHIP) using whole genome sequences from the TOPMed program.

A Fully-Adjusted Two-Stage Procedure for Rank Normalization in Genetic Association Studies

The paper introduces a fully-adjusted two-stage method for rank normalization in genetic association studies to reduce Type I errors and improve power by adjusting for covariates in both stages.

Efficient variant set mixed model association tests for continuous and binary traits in large-scale whole genome sequencing studies

The paper introduces SMMAT, a variant-set mixed model association test for continuous and binary traits in large-scale WGS studies, showing it controls type I error rates and applies to population structured and related samples.

Integrated Computing And Tracking System For Centralized High-Throughput Genetic Analysis: A Case Study

The paper describes an integrated computing and tracking system for high-throughput genetic analysis, demonstrating its utility in reproducible research with large, restricted data.