Please use this identifier to cite or link to this item: https://doi.org/10.1038/ncomms11307
Title: Fast and sensitive mapping of nanopore sequencing reads with GraphMap
Authors: Sovi?, I
Šiki?, M
Wilm, A
Fenlon, S.N
Chen, S 
Nagarajan, N 
Keywords: algorithm
bioinformatics
genome
mapping method
nanotechnology
precision
World Wide Web
accuracy
Article
error
genetic algorithm
GraphMap algorithm
human
human genome
nanopore
sequence analysis
single nucleotide polymorphism
algorithm
biology
genetics
genomics
high throughput sequencing
nanopore
procedures
reproducibility
sequence alignment
Algorithms
Computational Biology
Genome, Human
Genomics
High-Throughput Nucleotide Sequencing
Humans
Nanopores
Polymorphism, Single Nucleotide
Reproducibility of Results
Sequence Alignment
Issue Date: 2016
Publisher: Nature Publishing Group
Citation: Sovi?, I, Šiki?, M, Wilm, A, Fenlon, S.N, Chen, S, Nagarajan, N (2016). Fast and sensitive mapping of nanopore sequencing reads with GraphMap. Nature Communications 7 : 11307. ScholarBank@NUS Repository. https://doi.org/10.1038/ncomms11307
Rights: Attribution 4.0 International
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.
Source Title: Nature Communications
URI: https://scholarbank.nus.edu.sg/handle/10635/182483
ISSN: 2041-1723
DOI: 10.1038/ncomms11307
Rights: Attribution 4.0 International
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