Evidence map›Paper›PMID 26778510›Full record

ArticleScientific reports2016

An evaluation of the accuracy and speed of metagenome analysis tools.

Stinus Lindgreen, Karen L Adair, Paul P Gardner

Erratum issuedAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 170 papers.

0numbers the graph read from it
0cells of the map it votes in
170citing 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

170 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Metagenomic Assembly and Gene Prediction.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. A review of neural networks for metagenomic binning.Briefings in bioinformatics · 2025
    Review
  10. Article
  11. Article
  12. A survey of k-mer methods and applications in bioinformatics.Computational and structural biotechnology journal · 2024
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. CAIM: Coverage-based Analysis for Identification of Microbiome.bioRxiv : the preprint server for biology · 2024
    Article
  19. Review
  20. Article

110 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Stinus LindgreenBiomolecular Interaction Centre, University of Canterbury, Christchurch, New Zealand.
Karen L AdairBiomolecular Interaction Centre, University of Canterbury, Christchurch, New Zealand.
Paul P GardnerBiomolecular Interaction Centre, University of Canterbury, Christchurch, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metagenome studies are becoming increasingly widespread, yielding important insights into microbial communities covering diverse environments from terrestrial and aquatic ecosystems to human skin and gut. With the advent of high-throughput sequencing platforms, the use of large scale shotgun sequencing approaches is now commonplace. However, a thorough independent benchmark comparing state-of-the-art metagenome analysis tools is lacking. Here, we present a benchmark where the most widely used tools are tested on complex, realistic data sets. Our results clearly show that the most widely used tools are not necessarily the most accurate, that the most accurate tool is not necessarily the most time consuming, and that there is a high degree of variability between available tools. These findings are important as the conclusions of any metagenomics study are affected by errors in the predicted community composition and functional capacity. Data sets and results are freely available from http://www.ucbioinformatics.org/metabenchmark.html.

Indexed as

SoftwareComputational BiologyEcosystemGastrointestinal MicrobiomeHigh-Throughput Nucleotide SequencingHumansMetagenomeMetagenomicsSkin

Identifiers

PMID26778510
PMCPMC4726098

What OpenQuestion holds

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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.