High throughput DNA sequencing has revolutionized the study of both normal and disease tissues, including cancer. However, batch effects and other potential artifacts can hinder the accurate identification of copy number variations (CNVs) from DNA sequencing data. Issues that complicated CNV detection from single nucleotide polyporphism (SNP) array data can affect the analysis of DNA sequencing data (e.g. GC content). We therefore developed a novel method for improving normalization and CNV detection from exome sequencing data (Jiang et al, Nucleic Acids Res. 2015). This work was spearheaded by Yuchao Jiang while he was a graduate student rotating in our lab and was completed in collaboration with Dr. Nancy Zhang at Wharton. Version 2 has since been released by Dr. Jiang who is now a faculty member at the University of North Carolina.