Xizhi Luo

The paper identifies lung cancer susceptibility copy number variants (CNVs) and shows their potential role in genomic instability through association analyses and functional validation.

This paper introduces SPADE, a method for identifying spatially variable genes in spatial transcriptomic data, showing improved performance over existing methods in both within and between-group analyses.

OSCAA improves CNV-disease association analysis by integrating CNV detection and association testing in a single step, enhancing accuracy and power.

BMI-CNV improves CNV detection by integrating WES and microarray data across samples, showing better accuracy and identifying lung cancer risk regions.

This paper introduces LDcnv, a novel algorithm that improves copy number variation detection by integrating genomic correlation structure, showing higher accuracy and precision than existing methods.