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

By Heng Li, Richard Durbin. Bioinform., 2010

10,865 citations recorded by the source corpus.

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

Subfields: Artificial Intelligence, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/9de11759f7ce89f55fbc51e9d7aa6d7ee755c491

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Citations in the corpus

Geospatial Resolution of Human and Bacterial Diversity with City-Scale Metagenomics (2015, positive): “, 2014) and the Burrows-Wheeler Aligner (BWA) (Li and Durbin, 2010).”
Cell-free DNA comprises an in vivo nucleosome footprint that informs its tissues-of-origin (2016, neutral): “7.10 (Li and Durbin, 2010).”
LUMPY: a probabilistic framework for structural variant discovery (2012, methodology): “The read-pair module maps the output of a paired-end sequence alignment algorithm such as NOVOALIGN (C Hercus, unpublished) [8] or BWA [9], the split-read module maps the output of a split-read sequence alignment algorithm (for example, YAHA [10], BWA-SW [11], or BWA-MEM [5]), and the generic module”
Natural variation in genome architecture among 205 Drosophila melanogaster Genetic Reference Panel lines (2014, methodology): “melanogaster genome using BWA (Li and Durbin, 2010) and Novoalign (Novocraft.”
Benchmarking of Methods for Genomic Taxonomy (2014, methodology): “(a) Thereadsweremappedagainstthe16S database using the Smith-Waterman Burrows-Wheeler aligner (BWA) (27).”
Genome of an arbuscular mycorrhizal fungus provides insight into the oldest plant symbiosis (2013, methodology): “irregularis Gloin1 assembly using the Burrows-Wheeler Aligner (BWA) software package (9) with the default settings.”
A deep learning approach to pattern recognition for short DNA sequences (2018, methodology): “This suggests our approach of injecting random base-flipping noise at train time allows the DNNs to learn a more robust noise model than the one implicitly incorporated by aligners like BLAST and BWA by allowing gaps and mismatches to be tolerated.”
A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data (2011, methodology): “Again we sought to reduce mapping errors by remapping reads with BWA-SW to the 1000 Genomes Project phase-2 reference genome.”
An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge (2014, methodology): “Eight groups analyzed only the SOLiD WES data and four restricted their analysis to the Complete Genomics WGS data, often because of real or perceived difficulties with converting the extensible sequence format from the SOLiD runs into generic FASTQ files that would run on BWA, or unfamiliarity with”