Detecting Copy Number Variation via Next Generation Technology

Abstract

Copy number variants (CNVs), gains and losses of segments of genomic DNA associated with normal phenotypic variation and disease states, are traditionally detected using chromosomal microarrays. Recent bioinformatic advances now allow for the detection of CNVs using next generation sequencing (NGS) data, greatly increasing the clinical utility of NGS tests. Though not widespread, clinical diagnostic laboratories have started to implement CNV detection from targeted NGS gene panels and whole exome sequencing data, despite some limitations. Multiple tools have been designed to overcome these limitations, with some promising results. However, no single tool yet enables the high sensitivity and specificity needed to make it more than a supplementary assay for clinical laboratories. As sequencing costs drop and sequencing technologies improve, some of these shortcomings may be overcome by whole genome sequencing or long-read sequencing technologies. Here, we review methods used to detect CNVs from NGS data, including studies comparing their performance.