Yu Chen

This paper introduces rtPRS-CS, a real-time polygenic risk score method that dynamically updates predictions as new data streams in, improving accuracy for schizophrenia risk across diverse populations.

This paper introduces SuSiEx, a cross-population fine-mapping method that improves resolution and power by integrating data across ancestries, leading to more accurate identification of causal variants in complex traits and diseases.

This study uses T-SEM to identify gene expression patterns linked to genetic overlap and disorder-specific risk in psychiatric disorders, finding potential drug repurposing targets.

The paper uses cell-type deconvolution to analyze gene expression in schizophrenia and finds upper-layer neurons in the DLPFC are associated with SCZ risk.