UCLA

Abstract Background The characterization of structural variations (SV) such as insertions, deletions and copy number variations is a critical step in the process of understanding the full genetic architecture of organisms. Copy number variations (CNV) have attracted much recent attention due to their effects on gene expression and disease status. Results In this paper, we present a method that utilizes next-generation sequencing technologies (NGS), in order to both detect and reconstruct CNVs. We focus on a special type of CNV, namely tandemly organized de novo CNVs, which have been shown to occur with high frequency in the mouse genome. Conclusions We apply our method to CNV regions randomly inserted into the reference mouse genome and show that our method achieves good performance for both detection and reconstruction of tandemly organized de novo CNVs.