Evidence map›Paper›PMID 26020646›Full record

ArticlePLoS computational biology2015

Inferring horizontal gene transfer.

Matt Ravenhall, Nives Škunca, Florent Lassalle, Christophe Dessimoz

Abstract read
In one paragraph

Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 150 papers.

0numbers the graph read from it
0cells of the map it votes in
150citing 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

150 citing papers in PubMed.

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  13. A Gifsy prophage-encoded protein confers broad phage resistance inApplied and environmental microbiology · 2025
    Article
  14. Review
  15. Core genome expansion inIranian journal of microbiology · 2025
    Article
  16. Article
  17. Leveraging FracMinHash Containment for GenomicbioRxiv : the preprint server for biology · 2025
    Article
  18. The eukaryotic horizontal gene transfer dataset a compendium.bioRxiv : the preprint server for biology · 2025
    Article
  19. Closed genome sequence of anMicrobiology resource announcements · 2025
    Article
  20. Article

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

4 · The record

Corrections and comments

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

4 authors.

Matt RavenhallUniversity College London, London, United Kingdom.
Nives ŠkuncaETH Zurich, Zurich, Switzerland; Swiss Institute of Bioinformatics, Zurich, Switzerland.
Florent LassalleUniversity College London, London, United Kingdom.
Christophe DessimozUniversity College London, London, United Kingdom; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Horizontal or Lateral Gene Transfer (HGT or LGT) is the transmission of portions of genomic DNA between organisms through a process decoupled from vertical inheritance. In the presence of HGT events, different fragments of the genome are the result of different evolutionary histories. This can therefore complicate the investigations of evolutionary relatedness of lineages and species. Also, as HGT can bring into genomes radically different genotypes from distant lineages, or even new genes bearing new functions, it is a major source of phenotypic innovation and a mechanism of niche adaptation. For example, of particular relevance to human health is the lateral transfer of antibiotic resistance and pathogenicity determinants, leading to the emergence of pathogenic lineages. Computational identification of HGT events relies upon the investigation of sequence composition or evolutionary history of genes. Sequence composition-based ("parametric") methods search for deviations from the genomic average, whereas evolutionary history-based ("phylogenetic") approaches identify genes whose evolutionary history significantly differs from that of the host species. The evaluation and benchmarking of HGT inference methods typically rely upon simulated genomes, for which the true history is known. On real data, different methods tend to infer different HGT events, and as a result it can be difficult to ascertain all but simple and clear-cut HGT events.

Indexed as

Gene Transfer, HorizontalBase CompositionComputational BiologyComputer SimulationDatabases, GeneticDNA, BacterialDrug Resistance, BacterialEvolution, MolecularGenomicsHumansModels, GeneticModels, StatisticalPhylogenyDNA, Bacterial

Identifiers

PMID26020646
PMCPMC4462595

What OpenQuestion holds

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Registered trials

None linked

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.