ArticleBMC research notes2021
Shortcomings of SARS-CoV-2 genomic metadata.
Article in BMC research notes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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.
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.
Who cites it
23 citing papers in PubMed.
- Enriching Public Pathogen Genomic Records With Patient Metadata: Quantitative Study and Exploratory Case Analysis.JMIR bioinformatics and biotechnology · 2026Article
- An integrated framework for early detection and transmissibility assessment of emerging variants in wastewater.International journal of hygiene and environmental health · 2026Article
- A Metadata-Driven Framework for Strengthening Pathogen Genomics Lessons from SARS-CoV-2.medRxiv : the preprint server for health sciences · 2025Article
- The systematic assessment of completeness of public metadata accompanying omics studies in the Gene Expression Omnibus data repository.Genome biology · 2025Article
- Perceptual and technical barriers in sharing and formatting metadata accompanying omics studies.Cell genomics · 2025Review
- Genomic, socio-environmental, and sequencing capability patterns in the surveillance of SARS-CoV-2 in Latin America and the Caribbean up to 2023.Scientific reports · 2025Article
- Patient-Related Metadata Reported in Sequencing Studies of SARS-CoV-2: Protocol for a Scoping Review and Bibliometric Analysis.JMIR research protocols · 2025Article
- Integrating patient metadata and pathogen genomic data: advancing pandemic preparedness with a multi-parametric simulator.BMC research notes · 2025Article
- Observational
- Prediction models for COVID-19 disease outcomes.Emerging microbes & infections · 2024Article
- PHA4GE quality control contextual data tags: standardized annotations for sharing public health sequence datasets with known quality issues to facilitate testing and training.Microbial genomics · 2024Article
- Genomic Surveillance of SARS-CoV-2 in México: Three Years since Wuhan, China's First Reported Case.Viruses · 2023Article
- SARS-CoV-2 Variants of Concern and Clinical Severity in the Mexican Pediatric Population.Infectious disease reports · 2023Article
- Twenty-five years of Genomes OnLine Database (GOLD): data updates and new features in v.9.Nucleic acids research · 2023Article
- A review of SARS-CoV-2 drug repurposing: databases and machine learning models.Frontiers in pharmacology · 2023Review
- A collaborative approach to improving representation in viral genomic surveillance.PLOS global public health · 2023Article
- The DataHarmonizer: a tool for faster data harmonization, validation, aggregation and analysis of pathogen genomics contextual information.Microbial genomics · 2023Article
- Semantic interoperability: ontological unpacking of a viral conceptual model.BMC bioinformatics · 2022Article
- Challenges and Opportunities for Global Genomic Surveillance Strategies in the COVID-19 Era.Viruses · 2022Review
- A collaborative approach to improve representation in viral genomic surveillance.bioRxiv : the preprint server for biology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe SARS-CoV-2 pandemic has prompted one of the most extensive and expeditious genomic sequencing efforts in history. Each viral genome is accompanied by a set of metadata which supplies important information such as the geographic origin of the sample, age of the host, and the lab at which the sample was sequenced, and is integral to epidemiological efforts and public health direction. Here, we interrogate some shortcomings of metadata within the GISAID database to raise awareness of common errors and inconsistencies that may affect data-driven analyses and provide possible avenues for resolutions.
resultsOur analysis reveals a startling prevalence of spelling errors and inconsistent naming conventions, which together occur in an estimated ~ 9.8% and ~ 11.6% of "originating lab" and "submitting lab" GISAID metadata entries respectively. We also find numerous ambiguous entries which provide very little information about the actual source of a sample and could easily associate with multiple sources worldwide. Importantly, all of these issues can impair the ability and accuracy of association studies by deceptively causing a group of samples to identify with multiple sources when they truly all identify with one source, or vice versa.
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Registered trials
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.