tetano
Editor, Senior Moderator
PeerJ
. 2022 Apr 13;10:e13300.
doi: 10.7717/peerj.13300. eCollection 2022.
PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification
Renato R M Oliveira[SUP] #[/SUP][SUP] 1 2 [/SUP], Tatianne Costa Negri[SUP] #[/SUP][SUP] 1 [/SUP], Gisele Nunes[SUP] 1 [/SUP], Inácio Medeiros[SUP] 3 [/SUP], Guilherme Araújo[SUP] 3 4 [/SUP], Fabricio de Oliveira Silva[SUP] 1 [/SUP], Jorge Estefano Santana de Souza[SUP] 3 4 [/SUP], Ronnie Alves[SUP] 1 5 [/SUP], Guilherme Oliveira[SUP] 1 [/SUP]
Affiliations
Abstract
Motivation: Since the identification of the novel coronavirus (SARS-CoV-2), the scientific community has made a huge effort to understand the virus biology and to develop vaccines. Next-generation sequencing strategies have been successful in understanding the evolution of infectious diseases as well as facilitating the development of molecular diagnostics and treatments. Thousands of genomes are being generated weekly to understand the genetic characteristics of this virus. Efficient pipelines are needed to analyze the vast amount of data generated. Here we present a new pipeline designed for genomic analysis and variant identification of the SARS-CoV-2 virus.
Results: PipeCoV shows better performance when compared to well-established SARS-CoV-2 pipelines, with a lower content of Ns and higher genome coverage when compared to the Wuhan reference. It also provides a variant report not offered by other tested pipelines.
Availability: https://github.com/alvesrco/pipecov.
Keywords: Annotation; Covid19; Genomics; Pipeline; Sarscov2; Variant identification; Virus.
. 2022 Apr 13;10:e13300.
doi: 10.7717/peerj.13300. eCollection 2022.
PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification
Renato R M Oliveira[SUP] #[/SUP][SUP] 1 2 [/SUP], Tatianne Costa Negri[SUP] #[/SUP][SUP] 1 [/SUP], Gisele Nunes[SUP] 1 [/SUP], Inácio Medeiros[SUP] 3 [/SUP], Guilherme Araújo[SUP] 3 4 [/SUP], Fabricio de Oliveira Silva[SUP] 1 [/SUP], Jorge Estefano Santana de Souza[SUP] 3 4 [/SUP], Ronnie Alves[SUP] 1 5 [/SUP], Guilherme Oliveira[SUP] 1 [/SUP]
Affiliations
- PMID: 35437474
- PMCID: PMC9013232
- DOI: 10.7717/peerj.13300
Abstract
Motivation: Since the identification of the novel coronavirus (SARS-CoV-2), the scientific community has made a huge effort to understand the virus biology and to develop vaccines. Next-generation sequencing strategies have been successful in understanding the evolution of infectious diseases as well as facilitating the development of molecular diagnostics and treatments. Thousands of genomes are being generated weekly to understand the genetic characteristics of this virus. Efficient pipelines are needed to analyze the vast amount of data generated. Here we present a new pipeline designed for genomic analysis and variant identification of the SARS-CoV-2 virus.
Results: PipeCoV shows better performance when compared to well-established SARS-CoV-2 pipelines, with a lower content of Ns and higher genome coverage when compared to the Wuhan reference. It also provides a variant report not offered by other tested pipelines.
Availability: https://github.com/alvesrco/pipecov.
Keywords: Annotation; Covid19; Genomics; Pipeline; Sarscov2; Variant identification; Virus.