Evidence map›Paper›PMID 20376325›Full record

ArticlePloS one2010

A benchmark of parametric methods for horizontal transfers detection.

Jennifer Becq, Cécile Churlaud, Patrick Deschavanne

Abstract read
In one paragraph

Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

35 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. The Theory of Gene Family Histories.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  8. Article
  9. Indirect identification of horizontal gene transfer.Journal of mathematical biology · 2021
    Article
  10. Article
  11. Rewiring the specificity of extracytoplasmic function sigma factors.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  12. Article
  13. Article
  14. Article
  15. Genomic Analysis ofG3 (Bethesda, Md.) · 2019
    Article
  16. Article
  17. Review
  18. Alignment-Free Sequence Analysis and Applications.Annual review of biomedical data science · 2018
    Article
  19. Article
  20. Article
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

3 authors.

Jennifer BecqDynamique des Structures et Interactions des Macromolécules Biologiques, Institut National de la Santé et de la Recherche Médicale UMR-S 665, Université Paris Diderot, Institut National de la Transfusion Sanguine, Paris, France.
Cécile Churlaud
Patrick Deschavanne

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Horizontal gene transfer (HGT) has appeared to be of importance for prokaryotic species evolution. As a consequence numerous parametric methods, using only the information embedded in the genomes, have been designed to detect HGTs. Numerous reports of incongruencies in results of the different methods applied to the same genomes were published. The use of artificial genomes in which all HGT parameters are controlled allows testing different methods in the same conditions. The results of this benchmark concerning 16 representative parametric methods showed a great variety of efficiencies. Some methods work very poorly whatever the type of HGTs and some depend on the conditions or on the metrics used. The best methods in terms of total errors were those using tetranucleotides as criterion for the window methods or those using codon usage for gene based methods and the Kullback-Leibler divergence metric. Window methods are very sensitive but less specific and detect badly lone isolated gene. On the other hand gene based methods are often very specific but lack of sensitivity. We propose using two methods in combination to get the best of each category, a gene based one for specificity and a window based one for sensitivity.

Indexed as

Gene Transfer, HorizontalBase SequenceCodonComputational BiologyGenomicsMethodsModels, GeneticCodon

Identifiers

PMID20376325
PMCPMC2848678

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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.