Identification of Copy Number Alterations from Next-Generation Sequencing Data

Copy number variation (CNV), which is deletion and multiplication of segments of a genome, is an important genomic alteration that has been associated with many diseases including cancer. In cancer, CNVs are mostly somatic aberrations that occur during cancer evolution. Advances in sequencing technologies and arrival of next-generation sequencing data (whole-genome sequencing and whole-exome sequencing or targeted sequencing) have opened up an opportunity to detect CNVs with higher accuracy and resolution. Many computational methods have been developed for somatic CNV detection, which is a challenging task due to complexity of cancer sequencing data, high level of noise and biases in the sequencing process, and big data nature of sequencing data. Nevertheless, computational detection of CNV in sequencing data has resulted in the discovery of actionable cancer-specific CNVs to be used to guide cancer therapeutics, contributing to significant progress in precision oncology. In this chapter, we start by introducing CNVs. Then, we discuss the main approaches and methods developed for detecting somatic CNV for next-generation sequencing data, along with its challenges. Finally, we describe the overall workflow for CNV detection and introduce the most common publicly available software tools developed for somatic CNV detection and analysis.