GenAPI: a tool for gene absence-presence identification in fragmented bacterial genome sequences.
BMC Bioinformatics
; 21(1): 320, 2020 Jul 20.
Article
en En
| MEDLINE
| ID: mdl-32690023
BACKGROUND: Bacterial gene loss and acquisition is a well-known phenomenon which contributes to bacterial adaptation through changes in important phenotypes such as virulence, antibiotic resistance and metabolic capability. While advances in DNA sequencing have accelerated our ability to generate short genome sequence reads to disentangle phenotypic changes caused by gene loss and acquisition, the short-read genome sequencing often results in fragmented genome assemblies as a basis for identification of gene loss and acquisition events. However, sensitive and precise determination of gene content change for fragmented genome assemblies remains challenging as analysis needs to account for cases when only a fragment of the gene is assembled or when the gene assembly is split in more than one contig. RESULTS: We developed GenAPI, a command-line tool that is designed to compare the gene content of bacterial genomes for which only fragmented genome assemblies are available. GenAPI, unlike other available tools of similar purpose, accounts for imperfections in sequencing and assembly, and aims to compensate for them. We tested the performance of GenAPI on three different datasets to show that GenAPI has a high sensitivity while it maintains precision when dealing with partly assembled genes in both simulated and real datasets. Furthermore, we benchmarked the performance of GenAPI with six popular tools for gene presence-absence identification. CONCLUSIONS: Our developed bioinformatics tool, called GenAPI, has the same precision and recall rates when analyzing complete genome sequences as the other tools of the same purpose; however, GenAPI's performance is markedly better on fragmented genome assemblies.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Bacterias
/
Programas Informáticos
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Genoma Bacteriano
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Análisis de Secuencia de ADN
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Genómica
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Secuenciación de Nucleótidos de Alto Rendimiento
Tipo de estudio:
Diagnostic_studies
Idioma:
En
Revista:
BMC Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2020
Tipo del documento:
Article
País de afiliación:
Dinamarca
Pais de publicación:
Reino Unido