Signal processing based CNV detection in bacterial genomes

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU132855" target="_blank" >RIV/00216305:26220/19:PU132855 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-030-17938-0_9" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-17938-0_9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-17938-0_9" target="_blank" >10.1007/978-3-030-17938-0_9</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Signal processing based CNV detection in bacterial genomes

Popis výsledku v původním jazyce

Copy number variation (CNV) plays important role in drug resistance in bacterial genomes. It is one of the prevalent forms of structural variations which leads to duplications or deletions of regions with varying size across the genome. So far, most studies were concerned with CNV in eukaryotic, mainly human, genomes. The traditional laboratory methods as microarray genome hybridization or genotyping methods are losing its effectiveness with the omnipotent increase of fully sequenced genomes. Methods for CNV detection are predominantly targeted at eukaryotic sequencing data and only a few of tools is available for CNV detection in prokaryotic genomes. In this paper, we propose the CNV detection algorithm derived from state-of-the-art methods for peaks detection in the signal processing domain. The modified method of GC normalization with higher resolution is also presented for the needs of the CNV detection. The performance of the algorithms are discussed and analyzed.

Název v anglickém jazyce

Signal processing based CNV detection in bacterial genomes

Popis výsledku anglicky

Copy number variation (CNV) plays important role in drug resistance in bacterial genomes. It is one of the prevalent forms of structural variations which leads to duplications or deletions of regions with varying size across the genome. So far, most studies were concerned with CNV in eukaryotic, mainly human, genomes. The traditional laboratory methods as microarray genome hybridization or genotyping methods are losing its effectiveness with the omnipotent increase of fully sequenced genomes. Methods for CNV detection are predominantly targeted at eukaryotic sequencing data and only a few of tools is available for CNV detection in prokaryotic genomes. In this paper, we propose the CNV detection algorithm derived from state-of-the-art methods for peaks detection in the signal processing domain. The modified method of GC normalization with higher resolution is also presented for the needs of the CNV detection. The performance of the algorithms are discussed and analyzed.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20602 - Medical laboratory technology (including laboratory samples analysis; diagnostic technologies) (Biomaterials to be 2.9 [physical characteristics of living material as related to medical implants, devices, sensors])

Projekt

<a href="/cs/project/GA17-01821S" target="_blank" >GA17-01821S: Výkonnostní techniky pro sestavování a anotaci bakteriálního genomu využívající číslicové zpracování genomických signálů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Bioinformatics and Biomedical Engineering. IWBBIO 2019.

ISBN

978-3-030-17937-3

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

10

Strana od-do

93-102

Název nakladatele

Springer Verlag

Místo vydání

Granada, Spain

Místo konání akce

Granada

Datum konání akce

8. 5. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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