Liutiantian

Lecturer. Specializing in biostatistics, with a PhD from Shanghai Jiao Tong University. Primary research focus is on causal inference, mediation analysis, and the development of statistical methods and software programs for analyzing high throughput microbiome data and spatial transcriptome. Currently leading a project supported by the National Science Foundation for Young Scientists of China.

(1) Ruan, X., Cheng, Y., Ye, Y., Wang, Y., Chen, X., Yang, Y., ... & Yan, F. (2024). PIPET: predicting relevant subpopulations in single-cell data using phenotypic information from bulk data. Briefings in Bioinformatics, 25(4), bbae260.

(2) Zhu, J., Yang, J., Chen, X., Wang, Y., Wang, X., Zhao, M., ... & Jiang, L. (2024). Integrated Bulk and Single-cell RNA Sequencing Data Constructs and Validates a Prognostic Model for Non-small Cell Lung Cancer. Journal of Cancer, 15(3), 796.

(3) Liu, T., Zhou, C., Wang, H., Zhao, H., & Wang, T. (2022). phyloMDA: an R package for phylogeny-aware microbiome data analysis. BMC bioinformatics, 23(1), 213.

(4) Liu, T., Xu, P., Du, Y., Lu, H., Zhao, H., & Wang, T. (2022). MZINBVA: variational approximation for multilevel zero-inflated negative-binomial models for association analysis in microbiome surveys. Briefings in bioinformatics, 23(1), bbab443.

(5) Liu, T., Zhao, H., & Wang, T. (2020). An empirical Bayes approach to normalization and differential abundance testing for microbiome data. BMC bioinformatics, 21, 1-18.

Research on Omics Data-Driven Identification of Causal Biomarkers for Diseases within the Precision Medicine Framework

《Statistical calculation》chapter 6-7