Background:One of the most important and challenging issues in biomedicine and genomics is how to identify disease related genes.Datasets from high-throughput biotechnologies have been widely used to overcome this issue from various perspectives,e.g.,epigenomics,genomics,transcriptomics,proteomics,metabolomics.At the genomic level,copy number variations (CNVs) have been recognized as critical genetic variations,which contribute significantly to genomic diversity.They have been associated with both common and complex diseases,and thus have a large influence on a variety of Mendelian and somatic genetic disorders.Results:In this review,based on a variety of complex diseases,we give an overview about the critical role of using CNVs for identifying disease related genes,and discuss on details the different high-throughput and sequencing methods applied for CNV detection.Some limitations and challenges conceing CNV are also highlighted.Conclusions:Reliable detection of CNVs will not only allow discriminating driver mutations for various diseases,but also helps to develop personalized medicine when integrating it with other genomic features.