Evidence map›Paper›PMID 28073754›Full record

ArticleBioinformatics (Oxford, England)2017

Fast and accurate phylogeny reconstruction using filtered spaced-word matches.

Chris-André Leimeister, Salma Sohrabi-Jahromi, Burkhard Morgenstern

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Article
  2. A survey of k-mer methods and applications in bioinformatics.Computational and structural biotechnology journal · 2024
    Review
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  7. Review
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  9. Article
  10. NAR genomics and bioinformatics · 2021
    Article
  11. Article
  12. Article
  13. Sequence Comparison Without Alignment: The SpaM Approaches.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  14. Article
  15. Positional Correlation Natural Vector: A Novel Method for Genome Comparison.International journal of molecular sciences · 2020
    Article
  16. Article
  17. Article
  18. Article
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  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.

Chris-André LeimeisterDepartment of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, Goldschmidtstr. 1, 37077?Göttingen, Germany.
Salma Sohrabi-JahromiDepartment of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, Goldschmidtstr. 1, 37077?Göttingen, Germany.
Burkhard MorgensternDepartment of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, Goldschmidtstr. 1, 37077 Göttingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivation: Word-based or 'alignment-free' algorithms are increasingly used for phylogeny reconstruction and genome comparison, since they are much faster than traditional approaches that are based on full sequence alignments. Existing alignment-free programs, however, are less accurate than alignment-based methods. Results: We propose Filtered Spaced Word Matches (FSWM) , a fast alignment-free approach to estimate phylogenetic distances between large genomic sequences. For a pre-defined binary pattern of match and don't-care positions, FSWM rapidly identifies spaced word-matches between input sequences, i.e. gap-free local alignments with matching nucleotides at the match positions and with mismatches allowed at the don't-care positions. We then estimate the number of nucleotide substitutions per site by considering the nucleotides aligned at the don't-care positions of the identified spaced-word matches. To reduce the noise from spurious random matches, we use a filtering procedure where we discard all spaced-word matches for which the overall similarity between the aligned segments is below a threshold. We show that our approach can accurately estimate substitution frequencies even for distantly related sequences that cannot be analyzed with existing alignment-free methods; phylogenetic trees constructed with FSWM distances are of high quality. A program run on a pair of eukaryotic genomes of a few hundred Mb each takes a few minutes. Availability and Implementation: The program source code for FSWM including a documentation, as well as the software that we used to generate artificial genome sequences are freely available at http://fswm.gobics.de/. Contact: chris.leimeister@stud.uni-goettingen.de. Supplementary information: Supplementary data are available at Bioinformatics online.

Indexed as

AlgorithmsPhylogenyBase SequenceComputer SimulationGenome, BacterialGenome, PlantGenomicsSequence AlignmentSequence Analysis, DNASequence Homology, Nucleic AcidSoftwareTime Factors

Identifiers

PMID28073754
PMCPMC5409309

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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.