Overview

Bridging Statistics and Equity in Medical Genomics

Our research operates at the intersection of statistical methodology and large-scale omics, driven by a foundational commitment to representational equity in biomedical science.

We analyze high-dimensional omics data—including genomics and transcriptomics—to characterize the genetic architecture of complex traits. Concurrently, we develop statistical methods and computational pipelines that are mathematically rigorous, biologically interpretable, and equitable by design.

Going forward, a central focus of our laboratory is identifying and mathematically adjusting for selection bias in biomedical AI. The systematic underrepresentation of diverse ancestries and sex-stratified variations in training cohorts currently yields inequitable model performance across population strata. We aim to construct robust methodological frameworks that mitigate these biases, ensuring valid statistical inference and equitable applications across all diverse populations.

Publications

Selected Recent Works

📄 Journal Articles

First-author and corresponding-author only.   Co-First Corresponding Revision Invited

• COBRA: Cell-type-specific Orthogonal Batch effect Removal Algorithm in single cell RNA-sequencing data 2026 (accepted)Corresponding Seo S, Won S†, Park K†
  Bioinformatics
• Novel Genetic Loci for Nontuberculous Mycobacterial Pulmonary Disease and Potential Protective Effect of Body Mass Index 2025Co-First Park K*, Kim H*, Huh HJ*, Namkoong H, Hasegawa N, Nishimura T, Asakura T, Morimoto K, Kurashima A, Omae Y, Kawai Y, Tokunaga K, Cho J, Yim JJ, Won S†, Jhun BW†, Won HH†
  American Journal of Respiratory and Critical Care Medicine
• rs762855 Single Nucleotide Polymorphism Modulates the Risk for Diffuse-Type Gastric Cancer in Females: A Genome-Wide Association Study in the Korean Population 2025Co-First Park K*, Shin CM*, Song CH, Ohn JH, Lee S, Park JH, Yie GE, Kang SJ, Kim JS, Lee DH, Kim N†
  Gastric Cancer
• Single-Cell RNA Sequencing Reveals Transcriptional Changes in Circulating Immune Cells from Patients with Severe Asthma Induced by Biologics 2024Co-First Park K*, Lee JH*, Shin E, Jang HY, Song WJ, Kwon HS, Cho YS, Lee JE, Adcock I, Chung KF, Lee JS†, Won S†, Kim TB†
  Experimental & Molecular Medicine
• Genome-Wide Association Study Implicates the Role of TBXAS1 in the Pathogenesis of Depressive Symptoms among the Korean Population 2024 Park K, Do AR, Chung Y, Kim MJ, Rhee SJ, Yoon DH, Choi SH, Cho SJ, Kim HN†, Ahn YM†, Won S†
  Translational Psychiatry

* equally contributed · † corresponding author

🛠️ Software

• BALLI R Bartlett-Adjusted Likelihood-Based Linear model for Identifying differentially expressed genes in correlated RNA-seq data.
  Park K et al. · BMC Genomics 2019   GitHub →   Paper →
• COBRA R Cell-type-specific Orthogonal Batch effect Removal Algorithm for single-cell RNA-seq.
  Seo S, Won S†, Park K† · Under Review   GitHub →
• LASER R In Preparation Linear mixed-model framework for modeling Sample corrElation in RNA-seq differential expression analysis. Extends existing DEG frameworks to handle correlated sample structures at biobank scale.
  Park K†, Won S† · In Preparation   GitHub →

🔐 Patents

• Composition for predicting or diagnosing gastric cancer related to Helicobacter pylori infection comprising single nucleotide polymorphism detection agent 2025 Patent No. 10-2757562 · Republic of Korea
• Single nucleotide polymorphisms for the diagnosis of depression and uses thereof 2025 Patent No. 10-2883401 · Republic of Korea

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