Are we throwing away good data? Evaluation of chimera detection algorithms on long-read amplicons reveals high false-positive rates across algorithms.

Ali Hakimzadeh, Vladimir Mikryukov, Martin Metsoja, Leho Tedersoo, Sten Anslan

Abstract read

In one paragraph

Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Benchmarking of Reference-Based Tools for Strain-Level Resolution of Plant Microbiome.Molecular ecology resources · 2026
Article

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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.

Ali HakimzadehInstitute of Ecology and Earth Sciences, University of Tartu, Tartu, Estonia.

Vladimir MikryukovInstitute of Ecology and Earth Sciences, University of Tartu, Tartu, Estonia.

Martin MetsojaInstitute of Ecology and Earth Sciences, University of Tartu, Tartu, Estonia.

Leho TedersooInstitute of Ecology and Earth Sciences, University of Tartu, Tartu, Estonia.

Sten AnslanMycology and Microbiology Center, University of Tartu, Tartu, Estonia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long-read amplicon sequencing has enabled us to return to full-length DNA barcodes, which benefit from the higher taxonomic resolution in metabarcoding-based biodiversity studies. However, chimeric sequences (artificial constructs formed when incomplete amplicons fuse during polymerase chain reaction (PCR)) remain challenging, potentially skewing diversity estimates and ecological inferences. Here, we benchmark three

Indexed as

AlgorithmsDNA Barcoding, TaxonomicDetection AlgorithmsFalse Positive ReactionsPolymerase Chain ReactionSequence Analysis, DNABioinformaticsDe novo chimera detectionInternal transcribed spacerLong-read sequencingMetabarcodingrRNA

Identifiers

PMID41368503

DOI10.7717/peerj.20456

PMCPMC12684403

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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.