Xingyi Chen

This paper introduces IsoVita, a framework for learning interpretable compositional features from continuous covariates, showing improved detection of temporal isoform variation in human brain RNA-seq data.

This paper evaluates how different evaluation designs affect cross-donor generalization in single-cell classification, finding that random cell-level splitting overestimates performance compared to donor-held-out evaluation.

SpotSweeper-py provides spatially-aware quality control metrics for spatial omics data in Python, improving accuracy by reducing false positives and preserving tissue-specific architecture.