Zhongxuan Sun

PETRO improves Perturb-seq analysis by reducing off-target bias and enabling robust target-level perturbation effect estimation.

ADAPRE infers causal gene regulatory networks from Perturb-seq data by using adaptive instrumental variable modeling, improving accuracy over existing methods.

This paper introduces BasCoD, a framework for selecting optimal backgrounds in contrastive dimension reduction, improving contrast and interpretability in single-cell data.

This study performs the first GWAS on a latent partner choice index using 206,617 individuals, identifying genetic correlates and solutions to reduce assortative mating biases in genetic studies.

This paper introduces a statistical framework to optimize and benchmark polygenic risk scores using GWAS summary statistics, showing improved performance over existing methods.

This study identifies risks of false positives in ML-assisted GWAS and introduces POP-GWAS, a framework that provides valid inference for GWAS on ML-imputed phenotypes, applied to BMD data to find 89 novel loci.

This study identifies biases in proxy GWAS using parental Alzheimer's history, showing misleading genetic correlations and highlighting design issues in biobank cohorts.

This study re-examines genetic selective migration in the UK by analyzing migration patterns rather than place types, finding evidence of genetic selection in migration behavior.