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Nat Commun. 2016 Apr 15;7:11307. doi: 10.1038/ncomms11307.

Fast and sensitive mapping of nanopore sequencing reads with GraphMap.

Author information

1
Computational &Systems Biology, Genome Institute of Singapore, 60 Biopolis Street, #02-01 Genome, Singapore 138672, Singapore.
2
Centre for Informatics and Computing, Ruđer Bošković Institute, Bijenička 54, 10000 Zagreb, Croatia.
3
Faculty of Electrical Engineering and Computing, Department of Electronic Systems and Information Processing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia.
4
Bioinformatics Institute, Singapore 138671, Singapore.
5
Faculty of Medicine and Institute for Life Sciences, University of Southampton, Southampton SO16 6YD, UK.
6
Division of Infectious Diseases, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119074, Singapore.

Abstract

Realizing the democratic promise of nanopore sequencing requires the development of new bioinformatics approaches to deal with its specific error characteristics. Here we present GraphMap, a mapping algorithm designed to analyse nanopore sequencing reads, which progressively refines candidate alignments to robustly handle potentially high-error rates and a fast graph traversal to align long reads with speed and high precision (>95%). Evaluation on MinION sequencing data sets against short- and long-read mappers indicates that GraphMap increases mapping sensitivity by 10-80% and maps >95% of bases. GraphMap alignments enabled single-nucleotide variant calling on the human genome with increased sensitivity (15%) over the next best mapper, precise detection of structural variants from length 100 bp to 4 kbp, and species and strain-specific identification of pathogens using MinION reads. GraphMap is available open source under the MIT license at https://github.com/isovic/graphmap.

PMID:
27079541
PMCID:
PMC4835549
DOI:
10.1038/ncomms11307
[Indexed for MEDLINE]
Free PMC Article

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