Evidence map›Paper›PMID 36112351›Full record

ArticleJournal of computational biology : a journal of computational molecular cell biology2023

Novel Network Method Major Minor Variation Clustering Enables Identification of Poliovirus Clusters with High-Resolution Linkages.

Jiahui Tan, Yutong Zhao, Cara C Burns, Dechao Tian, Kun Zhao

Open access · greenAbstract read
In one paragraph

Article in Journal of computational biology : a journal of computational molecular cell biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 79% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 institutions in 2 countries.

Jiahui TanSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Yutong ZhaoSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Cara C BurnsPolio and Picornavirus Laboratory Branch, Division of Viral Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Dechao TianSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Kun ZhaoPolio and Picornavirus Laboratory Branch, Division of Viral Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.ORCID 0000-0002-4479-1102
Sun Yat-sen University · CNCenters for Disease Control and Prevention · US

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

The Global Polio Eradication Initiative uses an outbreak response protocol that defines type 2 Sabin or Sabin-like virus as those with 0-5 nucleotides diverging from their parental strain in the complete VP1 genomic region. Sabin or Sabin-like viruses share highly similar genome sequences, regardless of their origin. Thus, it is challenging to distinguish viruses at a higher resolution to detect polio clusters or trace sources for local transmissions of viruses at an early stage. To identify type 2 Sabin or Sabin-like sources and improve our ability to map viral sources to campaigns during the polio endgame, we investigated the feasibility of a new method for genetic sequence analysis. We named the method Major Minor Variation Clustering (MMVC), which uses a network model to simultaneously incorporate sequence similarity in major and minor variants in addition to onset dates to detect fine-scale polio clusters. Each identified cluster represents a collection of sequences that are highly similar in both major and minor variants, enabling the discovery of new links between viruses. By applying the method to a published data set collected in Nigeria during 2009-2012, we found that clusters identified using this method have several improvements over clusters derived from a phylogenetic tree approach. Integrative data analysis reveals that sequences in the same cluster have greater genomic similarities and better agreement with onset dates. As a complement to current phylogenetic tree approaches, MMVC has the potential to improve epidemiological surveillance and investigation precision to guide polio eradication.

Indexed as

PoliomyelitisPoliovirusCluster AnalysisGenomicsHumansPhylogenygenomic epidemiologynetwork modelingpolio eradicationwhole genome sequencing

Identifiers

PMID36112351
PMCPMC11299649
OpenAlexW4296029676

What OpenQuestion holds

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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.