Evidence map›Paper›PMID 24700317›Full record

ArticleBioinformatics (Oxford, England)2014

Fast alignment-free sequence comparison using spaced-word frequencies.

Chris-Andre Leimeister, Marcus Boden, Sebastian Horwege, Sebastian Lindner, Burkhard Morgenstern

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing 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

62 citing papers in PubMed.

  1. Article
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  7. Effects of spaced k-mers on alignment-free genotyping.Bioinformatics (Oxford, England) · 2023
    Article
  8. Article
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  12. Sequence Comparison Without Alignment: The SpaM Approaches.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  13. An Information-Entropy Position-WeightedFrontiers in genetics · 2021
    Article
  14. Article
  15. Article
  16. Article
  17. Positional Correlation Natural Vector: A Novel Method for Genome Comparison.International journal of molecular sciences · 2020
    Article
  18. Article
  19. Article
  20. Article

2 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

5 authors.

Chris-Andre LeimeisterDepartment of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, 37073 Göttingen, Germany and Université d'Évry Val d'Essonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA, 91037 Évry, France.
Marcus BodenDepartment of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, 37073 Göttingen, Germany and Université d'Évry Val d'Essonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA, 91037 Évry, France.
Sebastian HorwegeDepartment of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, 37073 Göttingen, Germany and Université d'Évry Val d'Essonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA, 91037 Évry, France.
Sebastian LindnerDepartment of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, 37073 Göttingen, Germany and Université d'Évry Val d'Essonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA, 91037 Évry, France.
Burkhard MorgensternDepartment of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, 37073 Göttingen, Germany and Université d'Évry Val d'Essonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA, 91037 Évry, FranceDepartment of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, 37073 Göttingen, Germany and Université d'Évry Val d'Essonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA, 91037 Évry, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationAlignment-free methods for sequence comparison are increasingly used for genome analysis and phylogeny reconstruction; they circumvent various difficulties of traditional alignment-based approaches. In particular, alignment-free methods are much faster than pairwise or multiple alignments. They are, however, less accurate than methods based on sequence alignment. Most alignment-free approaches work by comparing the word composition of sequences. A well-known problem with these methods is that neighbouring word matches are far from independent.

resultsTo reduce the statistical dependency between adjacent word matches, we propose to use 'spaced words', defined by patterns of 'match' and 'don't care' positions, for alignment-free sequence comparison. We describe a fast implementation of this approach using recursive hashing and bit operations, and we show that further improvements can be achieved by using multiple patterns instead of single patterns. To evaluate our approach, we use spaced-word frequencies as a basis for fast phylogeny reconstruction. Using real-world and simulated sequence data, we demonstrate that our multiple-pattern approach produces better phylogenies than approaches relying on contiguous words. AVAILABILITY AND IMPLEMENTATION: Our program is freely available at http://spaced.gobics.de/.

Indexed as

PhylogenyAlgorithmsAnimalsGenome, MitochondrialGenome, PlantGenomicsPrimatesSequence AlignmentSequence Analysis, DNASequence Analysis, Protein

Identifiers

PMID24700317
PMCPMC4080745

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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.