Evidence map›Paper›PMID 32353474›Full record

ArticleGenomics2020

Genotyping coronavirus SARS-CoV-2: methods and implications.

Changchuan Yin

Open access · greenAbstract read
In one paragraph

Article in Genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 170 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
170citing papers in PubMed, 2 pooled it
8.6field-weighted citation impact, top 2% 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

170 citing papers in PubMed, 2 syntheses or guidelines pooled it, 348 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  4. Review
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  10. Motifs in SARS-CoV-2 evolution.RNA (New York, N.Y.) · 2023
    Article
  11. Article
  12. Emerging Dominant SARS-CoV-2 Variants.Journal of chemical information and modeling · 2023
    Article
  13. Article
  14. Review
  15. Article
  16. All Microbiological Aspects of SARS-CoV-2 Virus.The Eurasian journal of medicine · 2022
    Article
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  18. Article
  19. Article
  20. Article

110 more citing papers are in PubMed but not listed here.

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

1 author at 1 institution in 1 country.

Changchuan YinDepartment of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, IL 60607, USA. Electronic address: cyin1@uic.edu.
University of Illinois Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emerging global infectious COVID-19 disease by novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) presents critical threats to global public health and the economy since it was identified in late December 2019 in China. The virus has gone through various pathways of evolution. To understand the evolution and transmission of SARS-CoV-2, genotyping of virus isolates is of great importance. This study presents an accurate method for effectively genotyping SARS-CoV-2 viruses using complete genomes. The method employs the multiple sequence alignments of the genome isolates with the SARS-CoV-2 reference genome. The single-nucleotide polymorphism (SNP) genotypes are then measured by Jaccard distances to track the relationship of virus isolates. The genotyping analysis of SARS-CoV-2 isolates from the globe reveals that specific multiple mutations are the predominated mutation type during the current epidemic. The proposed method serves an effective tool for monitoring and tracking the epidemic of pathogenic viruses in their global and local genetic variations. The genotyping analysis shows that the genes encoding the S proteins and RNA polymerase, RNA primase, and nucleoprotein, undergo frequent mutations. These mutations are critical for vaccine development in disease control.

Indexed as

GenomicsMutationPolymorphism, Single NucleotideBetacoronavirusCoronavirus InfectionsCOVID-19Evolution, MolecularGenome, ViralGenotyping TechniquesHumansPandemicsPneumonia, ViralSARS-CoV-2Sequence Alignment2019-nCoVCOVID-19GenotypingSARS-CoV-2Single-nucleotide polymorphism

Identifiers

PMID32353474
PMCPMC7184998
OpenAlexW3017703988

What OpenQuestion holds

Textmetadata
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.