Jin Jin, PhD

faculty photo
Assistant Professor of Biostatistics and Epidemiology
Department: Biostatistics and Epidemiology

Contact information
University of Pennsylvania
Perelman School of Medicine
Department of Biostatistics, Epidemiology and Informatics
203 Blockley Hall
423 Guardian Drive
Philadelphia, PA 19104-6021
Education:
BS (Statistics)
School for the Gifted Young, University of Science and Technology of China, Hefei, Anhui, China, 2014.
MS (Biostatistics)
University of Minnesota School of Public Health, Minneapolis, MN, 2016.
PhD (Biostatistics)
University of Minnesota School of Public Health, Minneapolis, MN, 2019.
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Description of Research Expertise

Statistical genetics, Bayesian statistics, predictive modeling, Mendelian randomization.

Selected Publications

Jin, J., Li, B., Wang, X., Yang, X., Li, Y., Wang, R., Ye, C., Shu, J., Fan, Z., Xue, F., Ge, T., Ritchie, M.D., Pasaniuc, B., Wojcik, G., Zhao, B.: PennPRS: a Centralized Cloud Computing Platform for Efficient Polygenic Risk Score Training in Precision Medicine. medRxiv Feb 2025 Notes: doi: 10.1101/2025.02.07.25321875.

Wang, R., Fang, L., Wang, Y., Jin, J.: Identifying Effect Modification of Latent Population Characteristics on Risk Factors with a Sparse Latent Factor Regression. bioRxiv Dec 2024 Notes: doi: 10.1101/2024.11.30.626101.

Zhao, Z., Dorn, S., Wu, Y., Yang, X., Jin, J., Lu, Q.: One Score to Rule Them All: Regularized Ensemble Polygenic Risk Prediction with GWAS Summary Statistics. bioRxiv Dec 2024 Notes: doi: 10.1101/2024.11.27.625748.

Yu, Y., Lakkis, A., Zhao, B., Jin, J.: Bayesian Mendelian Randomization Analysis for Latent Exposures Leveraging GWAS Summary Statistics for Traits Co-Regulated by the Exposures. bioRxiv Nov 2024 Notes: doi: 10.1101/2024.11.25.24317939.

Jin J, Chatterjee N.: Polygenic risk prediction for precision prevention. Handbook of Statistical Methods for Precision Medicine. CRC Press. Chapman and Hall/CRC, Page: 343-358, Oct 2024.

Roudbar, M.A., Vahedi, S.M., Jin, J., Jahangiri, M., Lanjanian, H., Habibi, D., Masjoudi, S., Riahi, P., Fateh, S.T., Neshati, F., Zahedi, A.S.: The effect of family structure on the still-missing heritability and genomic prediction accuracy of type 2 diabetes. Human genomics 18(1): 98, Sept 2024.

Wang, Y., Wang, Y., Jin, J.: A Graph Informed Framework Empowering Gene Pathway Discovery and Gene Expression-Assisted Disease Classification. bioRxiv Sept 2024 Notes: doi: 10.1101/2024.09.24.614661.

Zhang, J., Zhan, J., Jin, J., Ma, C., Zhao, R., O'Connell, J., Jiang, Y., Koelsch, B.L., Zhang, H., Chatterjee, N. and 23andMe Research Team: An ensemble penalized regression method for multi-ancestry polygenic risk prediction. Nature Communications 15(1): 3238, Apr 2024.

Jin, J., Zhan, J., Zhang, J., Zhao, R., O'Connell, J., Jiang, Y., Buyske, S., Gignoux, C., Haiman, C., Kenny, E.E. and Kooperberg, C: MUSSEL: Enhanced Bayesian polygenic risk prediction leveraging information across multiple ancestry groups. Cell Genomics 4(4): 100539, Apr 2024.

Dun, Y., Chatterjee, N., Jin, J. and Nishimura, A.: A Robust Bayesian Method for Building Polygenic Risk Scores using Projected Summary Statistics and Bridge Prior. arXiv Jan 2024 Notes: doi.org/10.48550/arXiv.2401.15014.

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Last updated: 03/07/2025
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