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Record W3136370540 · doi:10.2196/23015

Phylogenetic and Mutational Analysis of Lassa Virus Strains Isolated in Nigeria: Proposal for an In Silico Study

2021· article· en· W3136370540 on OpenAlexvenueno aff
Daniel Kolawole, Hayatu Raji, Malachy Ifeanyi Okeke

Bibliographic record

VenueJMIR Research Protocols · 2021
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsnot available
Fundersnot available
KeywordsLassa feverLassa virusIn silicoBiologyPhylogenetic treeGenomeVirologyGeneticsCladeVirusPhylogeneticsComputational biologyGene

Abstract

fetched live from OpenAlex

BACKGROUND: In 2018, the total number of Lassa fever cases in Nigeria was significantly higher than that observed in previous years. Hence, studies had attempted to determine the underlying cause. However, reports using phylogenetic methods to analyze this finding ruled out the emergence of potentially more transmissible Lassa virus strains or an increase in human-to-human viral transmission as the cause underlying the increase in cases. Two years later, the situation seems even worse as the number of confirmed cases has reached an all-time high according to situational reports released by the Nigerian Center for Disease Control. OBJECTIVE: Considering the increasing trend of Lassa fever cases and related mortality, the major objective of this study is to map mutations within the genomes of Lassa virus isolates from 2018 and 2019 using the reference sequence available at the National Center for Biotechnology Information as a benchmark and compare them to the genomes of viruses isolated during 1969-2017. This study would also attempt to identify a viral marker gene for easier identification and grouping. Finally, the time-scaled evolution of Lassa virus in Nigeria will be reconstructed. METHODS: After collecting the sequence data of Lassa virus isolates, Bayesian phylogenetic trees, a sequence identity matrix, and a single nucleotide polymorphism matrix will be generated using BEAST (version 2.6.2), Base-By-Base, and DIVEIN (a web-based tool for variant calling), respectively. RESULTS: Mining and alignment of Lassa virus genome sequences have been completed, while mutational analysis and the reconstruction of time-scaled maximum clade credibility trees, congruence tests for inferred segments, and gene phylogeny analysis are ongoing. CONCLUSIONS: The findings of this study would further the current knowledge of the evolutionary history of the Lassa virus in Nigeria and would document the mutations in Nigerian isolates from 1969 to 2019. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/23015.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.205
GPT teacher head0.560
Teacher spread0.355 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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