Evidence map›Paper›PMID 35437474›Full record

ArticlePeerJ2022

PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification.

Renato R M Oliveira, Tatianne Costa Negri, Gisele Nunes, Inácio Medeiros, Guilherme Araújo, Fabricio de Oliveira Silva, Jorge Estefano Santana de Souza, Ronnie Alves, Guilherme Oliveira

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.2field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Transmission dynamics ofFrontiers in public health · 2023
    Observational
  6. Article
  7. Article
  8. Sierra SARS-CoV-2 sequence and antiviral resistance analysis program.Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology · 2022
    Article
  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Renato R M Oliveira *Environmental Genomics, Instituto Tecnológico Vale, Belém, Pará, Brazil.ORCID 0000-0002-0111-8209
Tatianne Costa Negri *Environmental Genomics, Instituto Tecnológico Vale, Belém, Pará, Brazil.
Gisele NunesEnvironmental Genomics, Instituto Tecnológico Vale, Belém, Pará, Brazil.
Inácio MedeirosPrograma de Pós-Graduação em Bioinformática, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.
Guilherme AraújoPrograma de Pós-Graduação em Bioinformática, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.
Fabricio de Oliveira SilvaEnvironmental Genomics, Instituto Tecnológico Vale, Belém, Pará, Brazil.
Jorge Estefano Santana de SouzaPrograma de Pós-Graduação em Bioinformática, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.
Ronnie AlvesEnvironmental Genomics, Instituto Tecnológico Vale, Belém, Pará, Brazil.
Guilherme OliveiraEnvironmental Genomics, Instituto Tecnológico Vale, Belém, Pará, Brazil.ORCID 0000-0003-0054-3438
Vale Technological Institute · BRUniversidade Federal do Rio Grande do Norte · BRUniversidade Federal de Minas Gerais · BR

Funding

Biotechnology and Biological Sciences Research Council BB/P027849/1
6 · The paper itself

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.

Indexed as

COVID-19VirusesGenome, ViralGenomicsHumansSARS-CoV-2AnnotationCovid19GenomicsPipelineSarscov2Variant identificationVirus

Identifiers

PMID35437474
PMCPMC9013232
OpenAlexW4223916144

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.