ReviewMolecular ecology2025
In Vouchers We (Hope to) Trust: Unveiling Hidden Errors in GenBank's Tetrapod Taxonomic Foundations.
Review in Molecular ecology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Article
- Harnessing Deep Learning in Searching Wild Relatives of Domestic Animals.Molecular ecology resources · 2026Article
- Croaking for haste: How long does it take to describe a frog species since its discovery?PloS one · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Genetic repositories are invaluable resources foundational to various biological disciplines. While their data and metadata reliability are essential for robust research outcomes, numerous studies have highlighted data quality and consistency issues. Here, we detect and quantify errors at the most fundamental level by analysing the congruence of sequences derived from the same genetic marker and specimen voucher across tetrapods. Our analysis reveals that 32% of re-sequenced vouchers (with identical field or museum numbers) yield unequal sequences, ranging from a few mutations to significant divergences (0.06%-33.95%). These divergences may result from sample misidentification, labelling errors, fidelity disparities between sequencing methods, or contamination at various stages of the research process. Our findings demonstrate errors within GenBank at its most basal level and suggest that, although undetectable, a similar error rate likely exists in non-re-sequenced data. These previously overlooked errors are concerning because they arise from replicated experiments, which are uncommon, and raise serious questions about the reliability of non-re-sequenced specimens. Such errors can compromise the accuracy of biodiversity assessments (e.g., taxonomic assessment, eDNA and barcoding), phylogenetic analyses and conservation planning by artificially inflating the intraspecific divergence or misidentifying (to-be-described) species. Additionally, the accuracy of large-scale biological studies that rely on such data can be compromised. Our concerning results call for protocols ensuring sample traceability to the specimens or tissues during the whole process of data generation, analysis and deposition in a database. We propose a third-party annotation system for individual GenBank records that would allow flagging common errors and alert both the original submitter and all users to potential problems without modifying the original records.
Indexed as
Identifiers
What OpenQuestion holds
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.