Evidence map›Paper›PMID 40832245›Full record

ArticlebioRxiv : the preprint server for biology2025

Automated Annotation and Validation of Human Respiratory Virus Sequences using VADR.

Jeffrey Furlong, Stephanie Goya, Eric P Nawrocki, Vincent Calhoun, Eneida Hatcher, Linda Yankie, Alexander L Greninger

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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
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.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Jeffrey FurlongDepartment of Laboratory Medicine and Pathology, University of Washington Medical Center, Seattle, WA, 98109, USA.
Stephanie GoyaDepartment of Laboratory Medicine and Pathology, University of Washington Medical Center, Seattle, WA, 98109, USA.ORCID 0000-0001-7479-3064
Eric P NawrockiNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
Vincent CalhounNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
Eneida HatcherNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
Linda YankieNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
Alexander L GreningerDepartment of Laboratory Medicine and Pathology, University of Washington Medical Center, Seattle, WA, 98109, USA.ORCID 0000-0002-7443-0527

Funding

Automating Viral Genome Annotation and Quality Control for Viruses of Public Health ImportanceR03LM014965 · NLM · UNIVERSITY OF WASHINGTON · PI GRENINGER, ALEXANDER L · 2025 to 2025
$530k
NLM NIH HHS R03 LM014965
6 · The paper itself

Abstract

Accurate annotation of viral genomes is essential for reliable downstream analysis and public data sharing. While NCBI's Viral Annotation DefineR (VADR) pipeline provides standardized annotation and quality control, it only supports six viral groups to date. Here, we developed and validated 12 new reference sequence-based VADR models targeting key human respiratory viruses: measles virus, mumps virus, rubella virus, human metapneumovirus, human parainfluenza virus types 1-4, and seasonal coronaviruses (229E, NL63, OC43, HKU1). Model construction was guided by a comprehensive analysis of intra-species genomic and phylogenetic diversity, enabling the development of genotype-specific models associated with reference genomes that defined expected genome structure and annotation. Models were trained on 5,327 publicly available complete viral genomes and tested on 372 viral genomes not yet submitted to GenBank. VADR passed 96.3% of publicly available viral genomes and 98.1% of viral genomes not in the training set, correctly identifying overlapping ORFs, mature peptides, and transcriptional slippage as well as genome misassemblies. VADR detected novel viral biology including the first reported HCoV-OC43 NS2 knockout in a human infection and novel G and SH coding sequence lengths in human metapneumovirus. These VADR models are publicly available and are used by NCBI curators as part of the GenBank submission pipeline, supporting high-quality, scalable viral genome annotation for research and public health.

Identifiers

PMID40832245
PMCPMC12363772

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Registered trials

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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.