Methodological Papers

# Corresponding Author

• Jeon, H.#, Lim, K. S., Nguyen, Y., & Nettleton, D. (2023). Adjusting for gene-specific covariates to improve RNA-seq analysis. Bioinformatics, 39(8), btad498.

• Deng, Q.∗, Gupta, A.∗, Jeon, H.∗, Nam, J. H., Yilmaz, A. S., Chang, W., ... & Chung, D. (2023). graph-GPA 2.0: improving multi-disease genetic analysis with integration of functional annotation data. Frontiers in Genetics, 14. (∗: Joint first authors)

• Xie, J., Jeon, H., Xin, G., Ma, Q., & Chung, D. (2023). LRT: Integrative analysis of scRNAseq and scTCR-seq data to investigate clonal differentiation heterogeneity. PLOS Computational Biology, 19(7), e1011300.

• Jeon, H., Xie, J., Jeon, Y., Jung, K. J., Gupta, A., Chang, W., & Chung, D. (2023). Statistical Power Analysis for Designing Bulk, Single-Cell, and Spatial Transcriptomics Experiments: Review, Tutorial, and Perspectives. Biomolecules, 13(2), 221.

• Jeon, H.#, Nguyen, Y., Lim, K. S., & Nettleton, D. Improving genomic findings through information sharing between a pilot and main study. In preparation.

• Jeon, H.#, Nettleton, D. Case-specific tuning for random forest regression. In preparation.

• Jeon, H., Allen, C., Chang, Y., Xie, J., Ma, Q., & Chung, D. MAPLE: A hybrid framework for multi-sample spatial transcriptomics data. In preparation.

Collaborative and Applied Papers

• Dong, Q., Jeon, H., Lunney, J.K., Lim, K., Walker, K., Tuggle, C.K., Rowland, R.R.R., & Dekkers, J. Blood transcriptome response to vaccination and co-infection with porcine reproductive and respiratory virus and porcine circovirus in nursery pigs. Provisionally accepted in PLOS ONE.

• Denlinger, N., Song, N. J., Zhang, X., Jeon, H., Peterson, C., Wang, Y., ... & Yang, Y. (2024). Post-infusion PD-1+ CD8+ CAR-T cells identify patients responsive to CD19-CAR-T therapy in non-Hodgkin’ s lymphoma. Blood Advances.

• Savardekar, H., Allen, C., Jeon, H., Li, J., Quiroga, D., Schwarz, E., ... & Carson, W. E. (2024). Single-Cell RNA-Seq Analysis of Patient Myeloid-Derived Suppressor Cells and the Response to Inhibition of Bruton’s Tyrosine Kinase. Molecular Cancer Research, 22(3), 308-321.

• Song, N. J., Chakravarthy, K. B., Jeon, H., Bolyard, C., Reynolds, K., Weller, K. P., ... & Li, Z. (2024). mRNA vaccines against SARS-CoV-2 induce divergent antigen-specific T-cell responses in patients with lung cancer. Journal for ImmunoTherapy of Cancer, 12(1), e007922.

• Nagy, G., Diabate, M., Banerjee, T., Adamovich, A. I., Smith, N., Jeon, H., ... & Parvin, J. D. (2023). Multiplexed assay of variant effect reveals residues of functional importance in the BRCA1 coiled-coil and serine cluster domains. PLOS ONE, 18(11), e0293422.

• Song, M. A., Wold, L. E., Aslaner, D. M., Archer, K. J., Patel, D., Jeon, H., ... & Chung, S. (2023). Long-term impact of daily E-cigarette exposure on the lungs of asthmatic mice. Nicotine and Tobacco Research, ntad100.

• Erdélyi, D., Hatvani, I. G., Jeon, H., Jones, M., Tyler, J., & Kern, Z. (2023). Predicting spatial distribution of stable isotopes in precipitation by classical geostatistical-and machine learning methods. Journal of Hydrology, 617, 129129.

• Putz, E. J., Putz, A. M., Jeon, H., Lippolis, J. D., Ma, H., Reinhardt, T. A., & Casas, E. (2019). MicroRNA profiles of dry secretions through the first three weeks of the dry period from Holstein cows. Scientific Reports, 9(1), 1-9.

• SenNet OMICS Perspective Paper. In preparation.

Other Publications

• Jeon, H. (2022). An introduction to statistical methods: Differential gene expression analysis using    covariates. The Korean Statistical Society Newsletter, 11.

• Overview of Hyeongseon Jeon’ s Methodological and Team Science Research. Presented at Department of Biomedical Informatics, Columbus, OH, June 2024.

• Spatial Transcriptomic Analyses Of The Aging and IPF Lungs Reveals Age and Disease Senescence Niches. Presented at American Thoracic Society International Conference, San Diego, CA, May 2024.

• Adjusting for gene-specific covariates to improve rejection rules in RNA-seq differential expression analysis. Presented at University of North Carolina Wilmington, Department of Mathematics, Feb 2024.

• Adjusting for gene-specific covariates to improve rejection rules in RNA-seq differential expression analysis. Presented at Baruch College, Department of Information Systems and Statistics, Nov 2023.

• Adjusting for gene-specific covariates to improve rejection rules in RNA-seq differential expression analysis. Presented at Sungkyunkwan University, Department of Statistics, Oct 2023.

• Adjusting for gene-specific covariates to improve rejection rules in RNA-seq differential expression analysis. Presented at Joint Statistical Meetings 2023, Toronto, Canada, Aug 2023.

•  Adjusting for gene-specific covariates to improve rejection rules in RNA-seq differential expression analysis. Presented at Old Dominion University, Department of Mathematics and Statistics, Sep 2022.