ProcaryaSV: structural variation detection pipeline for bacterial genomes using short-read sequencing

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F24%3APU151775" target="_blank" >RIV/00216305:26220/24:PU151775 - isvavai.cz</a>

Result on the web

<a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-024-05843-1" target="_blank" >https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-024-05843-1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/s12859-024-05843-1" target="_blank" >10.1186/s12859-024-05843-1</a>

Result language

angličtina

Original language name

ProcaryaSV: structural variation detection pipeline for bacterial genomes using short-read sequencing

Original language description

BackgroundStructural variations play an important role in bacterial genomes. They can mediate genome adaptation quickly in response to the external environment and thus can also play a role in antibiotic resistance. The detection of structural variations in bacteria is challenging, and the recognition of even small rearrangements can be important. Even though most detection tools are aimed at and benchmarked on eukaryotic genomes, they can also be used on prokaryotic genomes. The key features of detection are the ability to detect small rearrangements and support haploid genomes. Because of the limiting performance of a single detection tool, combining the detection abilities of multiple tools can lead to more robust results. There are already available workflows for structural variation detection for long-reads technologies and for the detection of single-nucleotide variation and indels, both aimed at bacteria. Yet we are unaware of structural variations detection workflows for the short-reads sequencing platform. Motivated by this gap we created our workflow. Further, we were interested in increasing the detection performance and providing more robust results.ResultsWe developed an open-source bioinformatics pipeline, ProcaryaSV, for the detection of structural variations in bacterial isolates from paired-end short sequencing reads. Multiple tools, starting with quality control and trimming of sequencing data, alignment to the reference genome, and multiple structural variation detection tools, are integrated. All the partial results are then processed and merged with an in-house merging algorithm. Compared with a single detection approach, ProcaryaSV has improved detection performance and is a reproducible easy-to-use tool.ConclusionsThe ProcaryaSV pipeline provides an integrative approach to structural variation detection from paired-end next-generation sequencing of bacterial samples. It can be easily installed and used on Linux machines. It is publicly availab

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10600 - Biological sciences

Project

<a href="/en/project/GA23-05845S" target="_blank" >GA23-05845S: Real-time determination of infection threats from raw nanopore signals using machine learning techniques</a><br>

Continuities

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

Publication year

2024

Confidentiality

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

Name of the periodical

BMC BIOINFORMATICS

ISSN

1471-2105

e-ISSN

—

Volume of the periodical

25

Issue of the periodical within the volume

1

Country of publishing house

GB - UNITED KINGDOM

Number of pages

13

Pages from-to

1-13

UT code for WoS article

001268205500002

EID of the result in the Scopus database

2-s2.0-85198022812