Lingbo Zhou

ArcFISH identifies 3D genome features from multiplexed DNA FISH data by modeling axis-specific measurement errors, showing reliable detection of chromatin loops, TAD boundaries, and A/B compartments.

This study builds prediction models for RBC alloimmunization using statistical and machine learning methods on the REDS-III database, finding XGBoost provides the best performance with an AUC-ROC of 0.752.

The paper identifies eQTL and sQTL in African American blood cells, finding many rare variants undetected in European ancestry studies and creating an open database for results.