Research

Research Interests

My research interests are mainly in developing both theoretically sound and practically effective methods for causal inference with various statistical tools, including, but not limited to, model selection, constrained/regularized regression, high-dimensional data analysis, and data perturbation, as well as their applications in substantial real-world problems, mostly arising from genetics. I also actively collaborate with researchers from other disciplines.

Selected Publications

(Please see my Google Scholar for the full publication list.)

1. Xue, H., Shen, X., & Pan, W. (2023). Causal Inference in Transcriptome-Wide Association Studies with Invalid Instruments and GWAS Summary Data. Journal of the American Statistical Association, 1-27. (This paper won the 2022 ENAR Distinguished Student Paper Award.)

2. Lin, Z., Xue, H., & Pan, W. (2023). Combining Mendelian randomization and network de- convolution for inference of causal networks with GWAS summary data. PLoS genetics, 19(5), e1010762.

3. Lin, Z., Xue, H., & Pan, W. (2023). Robust multivariable Mendelian randomization based on constrained maximum likelihood. The American Journal of Human Genetics, 110(4), 592-605.

4. Xue, H., & Pan, W. (2022). Robust inference of bi-directional causal relationships in presence of correlated pleiotropy with GWAS summary data. PLoS genetics, 18(5), e1010205.

5. Xue, H., Shen, X., & Pan, W. (2021). Constrained maximum likelihood-based Mendelian ran- domization robust to both correlated and uncorrelated pleiotropic effects. The American Journal of Human Genetics, 108(7), 1251-1269.

6. Xue, H., & Pan, W. (2020). Inferring causal direction between two traits in the presence of horizontal pleiotropy with GWAS summary data. PLoS genetics, 16(11), e1009105.