The paper introduces PANIMaSTA, a method to construct minimally fragmented metagenomic pangenome graphs for highly diverse viral genomes, improving graph topology for comparative analysis.

bioRxiv · Oct 30, 2026 · PreprintBioinformatics

Severity-stratified, longitudinal cis-eQTL mapping enables high-sensitivity detection of candidate causal genes for critical COVID-19

Ernie Chen, Gisela Gabernet, David Brian Corry, Farrah Kheradmand, Lindsey Robert Baden, Rafick‐Pierre Sékaly, Grace A. McComsey, Elias K. Haddad, Charles B. Cairns, Nadine Rouphael, Ana Fernández-Sesma, Viviana R. Simon, Jordan Patrick Metcalf, Nelson Iván Agudelo Higuita, Catherine Lee Hough, , Dylan Duchen

This paper identifies 23 candidate causal genes for critical COVID-19 by integrating severity-stratified, longitudinal cis-eQTL mapping with GWAS signals from 1,031 patients.

medRxiv · Oct 21, 2026 · PreprintGenetic & Genomic Medicine

A hepatitis B virus (HBV) sequence variation graph improves sequence alignment and sample-specific consensus sequence construction for genetic analysis of HBV

Dylan Duchen, Steven J. Clipman, Candelaria Vergara, Chloe L. Thio, David L. Thomas, Priya Duggal, Genevieve L. Wojcik

This paper shows that using a genome graph instead of a linear reference improves HBV sequence alignment and sample-specific consensus sequence construction.

PLoS ONE · Apr 26, 2024Peer-reviewedGenomics

Genetic Susceptibility to Astrovirus Diarrhea in Bangladeshi Infants

Laura Chen, Rebecca M. Munday, Rashidul Haque, Dylan Duchen, Uma Nayak, Poonum S. Korpe, Alexander J. Mentzer, Beth D. Kirkpatrick, Genevieve L. Wojcik, William A. Petri, Priya Duggal

This study identifies two genetic regions associated with astrovirus diarrhea susceptibility in Bangladeshi infants through a genome-wide association study.

Open Forum Infectious Diseases · Feb 29, 2024Peer-reviewedGenetic & Genomic Medicine

Pathogen exposure misclassification can bias association signals in GWAS of infectious diseases when using population-based common controls

Dylan Duchen, Candelaria Vergara, Chloe L. Thio, Prosenjit Kundu, Nilanjan Chatterjee, David L. Thomas, Genevieve L. Wojcik, Priya Duggal

This study shows that using population-based common controls in GWAS of infectious diseases can lead to biased effect estimates and spurious associations due to unaccounted pathogen exposure.

medRxiv · Jul 14, 2022 · PreprintGenetic & Genomic Medicine