Evidence map›Paper›PMID 35259178›Full record

ArticlePloS one2022

Comparative analysis of alignment-free genome clustering and whole genome alignment-based phylogenomic relationship of coronaviruses.

Anastasiya D Kirichenko, Anastasiya A Poroshina, Dmitry Yu Sherbakov, Michael G Sadovsky, Konstantin V Krutovsky

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.5field-weighted citation impact, top 39% 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

7 citing papers in PubMed, 6 citations in OpenAlex.

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  6. Non-coding RNA in SARS-CoV-2: Progress toward therapeutic significance.International journal of biological macromolecules · 2022
    Review
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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

5 authors at 5 institutions in 2 countries.

Anastasiya D KirichenkoDepartment of Genomics and Bioinformatics, Institute of Fundamental Biology and Biotechnology, Siberian Federal University, Krasnoyarsk, Russian Federation.
Anastasiya A PoroshinaLaboratory of Molecular Systematics, Limnological Institute, Siberian Branch of Russian Academy of Sciences, Irkutsk, Russian Federation.
Dmitry Yu SherbakovLaboratory of Molecular Systematics, Limnological Institute, Siberian Branch of Russian Academy of Sciences, Irkutsk, Russian Federation.
Michael G SadovskyInstitute of Computational Modelling, Siberian Branch of Russian Academy of Sciences, Krasnoyarsk, Russian Federation.ORCID 0000-0002-1807-0715
Konstantin V KrutovskyDepartment of Genomics and Bioinformatics, Institute of Fundamental Biology and Biotechnology, Siberian Federal University, Krasnoyarsk, Russian Federation.ORCID 0000-0002-8819-7084
Bioinformatics Institute · RUKrasnoyarsk State Medical University · RUNovosibirsk State University · RUSiberian Branch of the Russian Academy of Sciences · RUVoronezh State University of Forestry and Technologies · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SARS-CoV-2 is the third coronavirus in addition to SARS-CoV and MERS-CoV that causes severe respiratory syndrome in humans. All of them likely crossed the interspecific barrier between animals and humans and are of zoonotic origin, respectively. The origin and evolution of viruses and their phylogenetic relationships are of great importance for study of their pathogenicity and development of antiviral drugs and vaccines. The main objective of the presented study was to compare two methods for identifying relationships between coronavirus genomes: phylogenetic one based on the whole genome alignment followed by molecular phylogenetic tree inference and alignment-free clustering of triplet frequencies, respectively, using 69 coronavirus genomes selected from two public databases. Both approaches resulted in well-resolved robust classifications. In general, the clusters identified by the first approach were in good agreement with the classes identified by the second using K-means and the elastic map method, but not always, which still needs to be explained. Both approaches demonstrated also a significant divergence of genomes on a taxonomic level, but there was less correspondence between genomes regarding the types of diseases they caused, which may be due to the individual characteristics of the host. This research showed that alignment-free methods are efficient in combination with alignment-based methods. They have a significant advantage in computational complexity and provide valuable additional alternative information on the genomes relationships.

Indexed as

Genome, ViralChromosome MappingCluster AnalysisComparative Genomic HybridizationCoronavirusHumansPhylogenySARS-CoV-2Sequence Alignment

Identifiers

PMID35259178
PMCPMC8903263
OpenAlexW4220899853

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.