Evidence map›Paper›PMID 28379292›Full record

ArticleBioinformatics (Oxford, England)2017

Kart: a divide-and-conquer algorithm for NGS read alignment.

Hsin-Nan Lin, Wen-Lian Hsu

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 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Mobile genomics: tools and techniques for tackling transposons.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020
    Review
  9. Article
  10. Article
  11. Article
  12. Minimap2: pairwise alignment for nucleotide sequences.Bioinformatics (Oxford, England) · 2018
    Article
  13. Review
  14. Article
  15. Article
  16. 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

2 authors.

Hsin-Nan LinInstitute of Information Science, Academia Sinica, Taipei, Taiwan.
Wen-Lian HsuInstitute of Information Science, Academia Sinica, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationNext-generation sequencing (NGS) provides a great opportunity to investigate genome-wide variation at nucleotide resolution. Due to the huge amount of data, NGS applications require very fast and accurate alignment algorithms. Most existing algorithms for read mapping basically adopt seed-and-extend strategy, which is sequential in nature and takes much longer time on longer reads.

resultsWe develop a divide-and-conquer algorithm, called Kart, which can process long reads as fast as short reads by dividing a read into small fragments that can be aligned independently. Our experiment result indicates that the average size of fragments requiring the more time-consuming gapped alignment is around 20 bp regardless of the original read length. Furthermore, it can tolerate much higher error rates. The experiments show that Kart spends much less time on longer reads than other aligners and still produce reliable alignments even when the error rate is as high as 15%. AVAILABILITY AND IMPLEMENTATION: Kart is available at https://github.com/hsinnan75/Kart/ . CONTACT: hsu@iis.sinica.edu.tw. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

SoftwareAlgorithmsGenetic VariationGenome, HumanHigh-Throughput Nucleotide SequencingHumansSequence AlignmentSequence Analysis, DNA

Identifiers

PMID28379292
PMCPMC5860120

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

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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.