Fast and accurate long-read alignment with Burrows-Wheeler transform.
Open accessAbstract
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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Bowtie2, BWA, HISAT2, STAR or any tool wrapping one of these aligners are confirmed to work for alignment to N-masked genomes.
“Software confirmed to be working for this approach include (but are not limited to) Bowtie2 11, BWA 12, HISAT2 13, STAR 14 or any tool wrapping one of these aligners.”
From SNPsplit: Allele-specific splitting of alignments between genomes with known SNP genotypes (2016) · cites this paper as [12]
The Implementation section identifies BWA-SW as a component of the BWA program, supporting the citation’s identification of BWA as an aligner. The paper discusses alignment to reference genomes but does not establish that BWA works for alignment to N-masked genomes; searches for N-masking and ambiguous bases found no such test or statement. (LLM, conf=0.84)
Experimental — accuracy not yet measuredMapping reads to specific genes is relatively straightforward with available bioinformatics tools, but using these tools to distinguish between reads derived from alternative alleles of the same gene remains challenging.
“Mapping reads to specific genes is relatively straightforward with the bioinformatics tools available today [10-13], but using these tools to distinguish between reads derived from alternative alleles of the same gene remains challenging [9].”
From Sources of bias in measures of allele-specific expression derived from RNA-seq data aligned to a single reference genome (2013) · cites this paper as [11]
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- Authors
- Li, H., & Durbin, R.
- Affiliations
- Wellcome Sanger Institute (GB)
- Corresponding author
- Durbin, Richard
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-01-15
- Volume
- 26
- Issue
- 5
- Pages
- 589-595
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC2828108
- OpenAlex
- W4247053599
- Cited by
- 12,063
- References
- 24
- Citations by year
- 2026: 639 · 2025: 972 · 2024: 1129 · 2023: 1067 · 2022: 1203 · 2021: 1245 · 2020: 1176 · 2019: 941 · 2018: 826 · 2017: 747 · 2016: 574 · 2015: 498 · 2014: 419 · 2013: 301 · 2012: 203
- FWCI
- 80.44
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by-nc)
- Funders
- Wellcome Trust (077192/Z/05/Z)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Computer Science › Artificial Intelligence › Algorithms and Data Compression
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
- Keywords
- long-read alignment, Burrows-Wheeler transform, Smith-Waterman alignment, sequence alignment, reference genome, blat, alignment speed, alignment accuracy, human genome
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