Liyang Song

cf-Cabernet improves cfDNA methylation sequencing by repairing nicks before end repair, preserving methylation information and outperforming standard methods.

The paper develops a Transformer-based model called cfAI to profile and detect cancer-derived cfDNA by integrating methylation, fragmentomics, and histone modifications, achieving high sensitivity and specificity in multi-cancer detection.

The paper introduces gsMap, a method that maps disease-relevant cells to human complex traits using spatial transcriptomics and GWAS data, revealing spatial patterns of schizophrenia and depression-associated glutamatergic neurons.

The paper introduces Cabernet, a bisulfite-free single-cell method for high-resolution 5mC and 5hmC profiling, revealing epigenetic dynamics in mouse embryos and demonstrating scalability for complex tissues.