CNproScan: Hybrid CNV detection for bacterial genomes

Discovering copy number variation (CNV) in bacteria is not in the spotlight compared to the attention focused on CNV detection in eukaryotes. However, challenges arising from bacterial drug resistance bring further interest to the topic of CNV and its role in drug resistance. General CNV detection methods do not consider bacteria's features and there is space to improve detection accuracy. Here, we present a CNV detection method called CNproScan focused on bacterial genomes. CNproScan implements a hybrid approach and other bacteria-focused features and depends only on NGS data. We benchmarked our method and compared it to the previously published methods and we can resolve to achieve a higher detection rate together with providing other beneficial features, such as CNV classification. Compared with other methods, CNproScan can detect much shorter CNV events.

Automated summary

CNV detection in bacteria is less focused on compared to eukaryotes, but with increasing interest due to challenges in bacterial drug resistance. CNproScan is a bacterial genome CNV detection method that can detect shorter events and provide classification, showing improvements over existing methods.