Evidence map›Paper›PMID 28200001›Full record

ArticleBioinformatics (Oxford, England)2017

Succinct colored de Bruijn graphs.

Martin D Muggli, Alexander Bowe, Noelle R Noyes, Paul S Morley, Keith E Belk, Robert Raymond, Travis Gagie, Simon J Puglisi, Christina Boucher

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 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing 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

51 citing papers in PubMed.

  1. Article
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  6. Movi Color: fast and accurate taxonomic classification with the move structure.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2025
    Article
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  8. Methods for Pangenomic Core Detection.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  9. Article
  10. Article
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  12. Article
  13. Article
  14. Microbial genomics · 2023
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Data Structures to Represent a Set ofACM computing surveys · 2022
    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

9 authors.

Martin D MuggliDepartment of Computer Science, Colorado State University, Fort Collins, CO, USA.
Alexander BoweDepartment of Informatics, National Institute of Informatics, Chiyoda-ku, Tokyo, Japan.
Noelle R NoyesDepartment of Clinical Sciences.
Paul S MorleyDepartment of Clinical Sciences.
Keith E BelkDepartment of Animal Sciences, Colorado State University, Fort Collins, CO, USA.
Robert RaymondDepartment of Computer Science, Colorado State University, Fort Collins, CO, USA.
Travis GagieSchool of Computer Science and Telecommunications, Diego Portales University and CEBIB, Santiago, Chile.
Simon J PuglisiDepartment of Computer Science, University of Helsinki, Helsinki, Finland.
Christina BoucherDepartment of Computer Science, Colorado State University, Fort Collins, CO, USA.

Funding

Veterinary Pre-Doctoral Research Scholars ProgramT32OD012201 · OD · COLORADO STATE UNIVERSITY · PI VANDEWOUDE, SUE · 2013 to 2019
$795k
NIH HHS T32 OD012201Wellcome Trust
6 · The paper itself

Abstract

motivationIn 2012, Iqbal et al. introduced the colored de Bruijn graph, a variant of the classic de Bruijn graph, which is aimed at 'detecting and genotyping simple and complex genetic variants in an individual or population'. Because they are intended to be applied to massive population level data, it is essential that the graphs be represented efficiently. Unfortunately, current succinct de Bruijn graph representations are not directly applicable to the colored de Bruijn graph, which requires additional information to be succinctly encoded as well as support for non-standard traversal operations.

resultsOur data structure dramatically reduces the amount of memory required to store and use the colored de Bruijn graph, with some penalty to runtime, allowing it to be applied in much larger and more ambitious sequence projects than was previously possible. AVAILABILITY AND IMPLEMENTATION: https://github.com/cosmo-team/cosmo/tree/VARI. CONTACT: martin.muggli@colostate.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

SoftwareAlgorithmsBacteriaEukaryotaGenotyping TechniquesSequence Analysis, DNA

Identifiers

PMID28200001
PMCPMC5872255

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.