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

Authors: Hsin-Nan Lin; Wen-Lian Hsu;

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

Abstract

Abstract Motivation Next-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. Results We 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/. Supplementary information Supplementary data are available at Bioinformatics online.

Related Organizations
Keywords

Genome, Human, Genetic Variation, High-Throughput Nucleotide Sequencing, Humans, Sequence Analysis, DNA, Original Papers, Sequence Alignment, Algorithms, Software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
39
Top 1%
Top 10%
Top 10%
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