Home  /  Data  /  Software  /  Misc  /  Github  /  E-mail   /  Twitter

Selected papers are below. For a full list of papers, please see Google Scholar.

Machine learning (ML)-assisted statistical inference

Machine learning is making predictions with uncertainty. How to make statistically rigorous scientific discovery with these "black-box" predictions?

Task-Agnostic Machine Learning-Assisted Inference
Miao J. and Lu Q. (2024).
[Preprint] [Software: PSPS]

Valid Inference for Machine Learning-Assisted GWAS
Miao J., Wu Y., Sun Z., Miao X., Lu T., Zhao J., Lu Q. (2024).
--Winner of the 2024 ICSA Student Paper Award
[Preprint] [Software: POP-TOOLS] [Summary]

Assumption-Lean and Data-Adaptive Post-Prediction Inference
Miao J.*, Miao X.*, Wu Y., Zhao J., Lu Q. (2023).
[Preprint] [Software: POPInf]

Heterogeneous treatment effect, gene-environment interactions, and genetic modifier

Transcriptome-Level Interpretation of Gene-by-Sex Interactions for Human Complex Traits
Miao J.*, Wu Y.*, Yang X., Schmitz L., Lu Q. (2024).
--Winner of the 2023 Charles J. Epstein Trainee Award for Excellence in Human Genetics Research Semifinalist

Reimagining Gene-Environment Interaction Analysis for Human Complex Traits
Miao J., Song G., Wu Y., Hu J., Wu Y., Basu S., Andrews J., Schaumberg K., Fletcher J., Schmitz L., Lu Q. (2022).
[Preprint] [Software: PIGEON] [Summary]

A Quantile Integral Linear Model to Quantify Genetic Effects on Phenotypic Variability
Miao J., Lin Y., Wu Y., Zheng B., Schmitz L., Fletcher J., Lu Q. (2022).
--Winner of the 2022 ASA Section on Statistics in Genomics and Genetics Student Paper Award
[Journal] [Preprint] [Software: QUAIL] [Summary]

Generalizability and fairness of genetically-informed risk prediction across diverse contexts

Quantifying Portable Genetic Effects and Improving Cross-Ancestry Genetic Prediction with GWAS Summary Statistics
Miao J.*, Guo H.*, Song G., Zhao Z., Hou L., Lu Q. (2023).
Nature Communications
[Journal] [Preprint] [Software: X-Wing] [Summary]