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Fast and accurate long-read alignment with Burrows–Wheeler transform

Heng Li; Richard Durbin · Bioinformatics · 2010

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Abstract Motivation: Many programs for aligning short sequencing reads to a reference genome have been developed in the last 2 years. Most of them are very efficient for short reads but inefficient or not applicable for reads >200 bp because the algorithms are heavily and specifically tuned for short queries with low sequencing error rate. However, some sequencing platforms already produce longer reads and others are expected to become available soon. For longer reads, hashing-based software such as BLAT and SSAHA2 remain the only choices. Nonetheless, these methods are substantially slower than short-read aligners in terms of aligned bases per unit time. Results: We designed and implemented a new algorithm, Burrows-Wheeler Aligner's Smith-Waterman Alignment (BWA-SW), to align long sequences up to 1 Mb against a large sequence database (e.g. the human genome) with a few gigabytes of memory. The algorithm is as accurate as SSAHA2, more accurate than BLAT, and is several to tens of times faster than both. Availability: http://bio-bwa.sourceforge.net Contact: rd@sanger.ac.uk

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APA 7

Li, H. & Durbin, R. (2010). Fast and accurate long-read alignment with Burrows–Wheeler transform. https://doi.org/10.1093/bioinformatics/btp698

MLA

Li, Heng, and Richard Durbin. "Fast and accurate long-read alignment with Burrows–Wheeler transform." 2010. https://doi.org/10.1093/bioinformatics/btp698.

Chicago

Li, Heng and Richard Durbin. 2010. "Fast and accurate long-read alignment with Burrows–Wheeler transform.". https://doi.org/10.1093/bioinformatics/btp698.

Harvard

Li, H. and Durbin, R. 2010, Fast and accurate long-read alignment with Burrows–Wheeler transform, Bioinformatics, available at: https://doi.org/10.1093/bioinformatics/btp698 [Accessed 9 Aug. 2026].

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Title
Fast and accurate long-read alignment with Burrows–Wheeler transform
Author / contributors
Heng Li; Richard Durbin
Publisher
Bioinformatics
Publication year
2010
Language
English

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