Yan Li

JUMP improves replicability analysis in high-dimensional data by controlling FDR and increasing power, applied to spatial transcriptomic datasets.

STAREG identifies replicable spatially variable genes across spatial transcriptomic studies using an empirical Bayesian approach with improved power and false discovery rate control.

The paper develops a method to improve statistical power in spatial transcriptomic analysis by integrating multi-omics data while controlling false discovery rate.

This study develops a framework to predict missing metadata in gene expression datasets to improve their reusability, outperforming standard metrics like F1-score.