* Indicates equal contribution as first author.
Published in Cell , 2026
This study develops a trans-regulatory gene mapping framework for identifying disease-driving genes in asthma by integrating statistical genetics with functional genomic validation.
Recommended citation: Salamone, I. M., Tian, P.*, Qi, Z., et al. (2026). "Trans-regulatory gene mapping prioritizes disease drivers in asthma." Cell.
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Published in Briefings in Bioinformatics , 2026
CoxMDS is a multiple data splitting framework for high-dimensional mediation analysis with survival outcomes. The method is designed to identify potential mediators while providing finite-sample false discovery rate control, including settings with correlated or non-Gaussian mediators.
Recommended citation: Yao, M., Tian, P.*, Li, X., et al. (2026). "CoxMDS: multiple data splitting for high-dimensional mediation analysis with survival outcomes in epigenome-wide studies." Briefings in Bioinformatics, 27(1), bbaf730.
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Published in Bioinformatics , 2024
TWAS-GKF is a knockoff-based method for identifying trait-associated genes in transcriptome-wide association studies. The method uses summary-level statistics and provides finite-sample false discovery rate control without requiring individual-level genotype data.
Recommended citation: Wang, A., Tian, P.*, Zhang, Y. D. (2024). "TWAS-GKF: a novel method for causal gene identification in transcriptome-wide association studies with knockoff inference." Bioinformatics, 40(8), btae502.
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Published in Communications Biology , 2023
This study investigates the shared genetic architecture between COVID-19 and venous thromboembolism using genome-wide cross-trait analyses and Mendelian randomization. The results provide evidence for shared genetic susceptibility and potential causal relationships between the two conditions.
Recommended citation: Huang, X., Yao, M., Tian, P., et al. (2023). "Genome-wide cross-trait analysis and Mendelian randomization reveal a shared genetic etiology and causality between COVID-19 and venous thromboembolism." Communications Biology, 6, 441.
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Published in BMC Bioinformatics , 2022
Grace-AKO is a high-dimensional variable selection method that combines graph-constrained estimation with aggregated knockoff inference. By incorporating prior gene network structures, the method improves selection stability while maintaining finite-sample false discovery rate control.
Recommended citation: Tian, P., Hu, Y., Liu, Z., Zhang, Y. D. (2022). "Grace-AKO: a novel and stable knockoff filter for variable selection incorporating gene network structures." BMC Bioinformatics, 23, 478.
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Published in Bioinformatics , 2022
CoxMKF is a knockoff-based framework for high-dimensional mediation analysis with survival outcomes. It combines multiple knockoffs with the Cox proportional hazards model to identify potential mediators while controlling the false discovery rate in finite samples.
Recommended citation: Tian, P.*, Yao, M.*, Huang, T., Liu, Z. (2022). "CoxMKF: a knockoff filter for high-dimensional mediation analysis with a survival outcome in epigenetic studies." Bioinformatics, 38(23), 5229–5235.
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Published in Frontiers in Genetics , 2022
This study develops TL-Multi, a transfer learning framework for polygenic risk prediction across diverse populations. The method leverages information from large European GWAS datasets to improve prediction accuracy in populations with smaller available sample sizes.
Recommended citation: Tian, P., Chan, T. H., Wang, Y.-F., Yang, W., Yin, G., Zhang, Y. D. (2022). "Multiethnic polygenic risk prediction in diverse populations through transfer learning." Frontiers in Genetics, 13, 906965.
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