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JUGAS, R. SEDLÁŘ, K. VÍTEK, M. NYKRÝNOVÁ, M. BARTOŇ, V. BEZDÍČEK, M. LENGEROVÁ, M. ŠKUTKOVÁ, H.
Original Title
CNproScan: Hybrid CNV detection for bacterial genomes
Type
journal article in Web of Science
Language
English
Original Abstract
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.
Keywords
Next-generation sequencing; Copy number variation; Bacteria; Drug resistance
Authors
JUGAS, R.; SEDLÁŘ, K.; VÍTEK, M.; NYKRÝNOVÁ, M.; BARTOŇ, V.; BEZDÍČEK, M.; LENGEROVÁ, M.; ŠKUTKOVÁ, H.
Released
3. 7. 2021
Publisher
Elsevier
ISBN
0888-7543
Periodical
GENOMICS
Year of study
113
Number
5
State
United States of America
Pages from
3103
Pages to
3111
Pages count
9
URL
https://www.sciencedirect.com/science/article/abs/pii/S0888754321002779
BibTex
@article{BUT172131, author="Robin {Jugas} and Karel {Sedlář} and Martin {Vítek} and Markéta {Jakubíčková} and Vojtěch {Bartoň} and Matěj {Bezdíček} and Martina {Lengerová} and Helena {Vítková}", title="CNproScan: Hybrid CNV detection for bacterial genomes ", journal="GENOMICS", year="2021", volume="113", number="5", pages="3103--3111", doi="10.1016/j.ygeno.2021.06.040", issn="0888-7543", url="https://www.sciencedirect.com/science/article/abs/pii/S0888754321002779" }