Cited by 58,607Genomics and Phylogenetic StudiesAlgorithms and Data CompressionFractal and DNA sequence analysis

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Fast and accurate short read alignment with Burrows-Wheeler transform

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Li, Heng, Durbin, Richard·2009·Bioinformatics

DOI 10.1093/bioinformatics/btp324PMC PMC2705234

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Abstract

MOTIVATION: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. RESULTS: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows-Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is approximately 10-20x faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. AVAILABILITY: http://maq.sourceforge.net.

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Fig. 1. Prefix trie of string ‘GOOGOL’. Symbol ∧ marks the start of the string. The two numbers in a node give the SA interval of the string represented by the node (see Section 2.3). The dashed line shows the route of the brute-force search for a query string ‘LOL’, allowing at most one mismatch. Edge labels in squares mark the mismatches to the query in searching. The only hit is the bold node [1, 1] which represents string ‘GOL’.CC BY-NC · PubMed Central

Fig. 2. Constructing suffix array and BWT string for X=googol$. String X is circulated to generate seven strings, which are then lexicographically sorted. After sorting, the positions of the first symbols form the suffix array (6, 3, 0, 5, 2, 4, 1) and the concatenation of the last symbols of the circulated strings gives the BWT string lo$oogg.CC BY-NC · PubMed Central

Fig. 3. Algorithm for inexact search of SA intervals of substrings that match W. Reference X is $ terminated, while W is A/C/G/T terminated. Procedure InexactSearch(W, z) returns the SA intervals of substrings that match W with no more than z differences (mismatches or gaps); InexRecur(W, i, z, k, l) recursively calculates the SA intervals of substrings that match W[0, i] with no more than z differences on the condition that suffix Wi+1 matches interval [k, l]. Lines started with asterisk are for insertions to and deletions from X, respectively. D(i) is the lower bound of the number of differences in string W[0, i].CC BY-NC · PubMed Central

Fig. 4. Equivalent algorithm to calculate D(i).CC BY-NC · PubMed Central

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Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
Altschul, S. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.17.3389 · Cited by 73,302
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
Self-citation
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
Improved tools for biological sequence comparison.
Pearson, W. R., & Lipman, D. J. (1988) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.85.8.2444 · Cited by 11,227
<tt>BLAT</tt> —The <tt>BLAST</tt> -Like Alignment Tool
Kent, W. J. (2002) · Genome Research · doi:10.1101/gr.229202 · Cited by 8,480
A Greedy Algorithm for Aligning DNA Sequences
Zhang, Z., Schwartz, S., Wagner, L., & Miller, W. (2000) · Journal of Computational Biology · doi:10.1089/10665270050081478 · Cited by 5,459
Real-Time DNA Sequencing from Single Polymerase Molecules
Eid, J., Fehr, A., Gray, J., Luong, K., Lyle, J., Otto, G., Peluso, P., Rank, D., Baybayan, P., Bettman, B., et al. (2009) · Science · doi:10.1126/science.1162986 · Cited by 3,732
SOAP: Short oligonucleotide alignment program
Li, R., Li, Y., Kristiansen, K., & Wang, J. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn025 · Cited by 3,597
Mapping short DNA sequencing reads and calling variants using mapping quality scores
Li, H., Ruan, J., & Durbin, R. (2008) · Genome Research · doi:10.1101/gr.078212.108 · Cited by 2,638
Self-citation
A Block-sorting Lossless Data Compression Algorithm
Burrows, M. T., & Wheeler, D. J. (1994) · Cited by 2,333

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Berger, M. F., Levin, J. Z., Vijayendran, K., Sivachenko, A., Adiconis, X., Maguire, J., Johnson, L. A., Robinson, J., Verhaak, R. G., Sougnez, C., et al. (2010) · Genome Research · doi:10.1101/gr.103697.109 · Cited by 305
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Cuomo, A. S. E., Seaton, D. D., McCarthy, D. J., Martinez, I., Bonder, M. J., Garcia-Bernardo, J., Amatya, S., Madrigal, P., Isaacson, A., Buettner, F., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-14457-z · Cited by 331
Self-citation
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Bahr, C., von Paleske, L., Uslu, V. V., Remeseiro, S., Takayama, N., Ng, S. W., Murison, A., Langenfeld, K., Petretich, M., Scognamiglio, R., et al. (2018) · Nature · doi:10.1038/nature25193 · Cited by 328
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Thomas, C. A., Tejwani, L., Trujillo, C. A., Negraes, P. D., Herai, R. H., Mesci, P., Macia, A., Crow, Y. J., & Muotri, A. R. (2017) · Cell Stem Cell · doi:10.1016/j.stem.2017.07.009 · Cited by 330
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Chandra, T., Kirschner, K., Thuret, J.-Y., Pope, B. D., Ryba, T., Newman, S., Ahmed, K., Samarajiwa, S. A., Salama, R., Carroll, T., et al. (2012) · Molecular Cell · doi:10.1016/j.molcel.2012.06.010 · Cited by 308
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Raghavan, M., DeGiorgio, M., Albrechtsen, A., Moltke, I., Skoglund, P., Korneliussen, T. S., Grønnow, B., Appelt, M., Gulløv, H. C., Friesen, T. M., et al. (2014) · Science · doi:10.1126/science.1255832 · Cited by 329
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Schubert, M., Ginolhac, A., Lindgreen, S., Thompson, J. F., AL-Rasheid, K. A., Willerslev, E., Krogh, A., & Orlando, L. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-178 · Cited by 325
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Nookaew, I., Papini, M., Pornputtapong, N., Scalcinati, G., Fagerberg, L., Uhlén, M., & Nielsen, J. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks804 · Cited by 309
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Vincent, B. M., Lancaster, A. K., Scherz-Shouval, R., Whitesell, L., & Lindquist, S. (2013) · PLoS Biology · doi:10.1371/journal.pbio.1001692 · Cited by 322
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Liu, S., Huang, S., Chen, F., Zhao, L., Yuan, Y., Francis, S. S., Fang, L., Li, Z., Lin, L., Liu, R., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.016 · Cited by 279
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Wang, G.-D., Zhai, W., Yang, H.-C., Fan, R.-X., Cao, X., Zhong, L., Wang, L., Liu, F., Wu, H., Cheng, L.-G., et al. (2013) · Nature Communications · doi:10.1038/ncomms2814 · Cited by 323
Clostridium scindens: a human gut microbe with a high potential to convert glucocorticoids into androgens
Ridlon, J. M., Ikegawa, S., Alves, J. M. P., Zhou, B., Kobayashi, A., Iida, T., Mitamura, K., Tanabe, G., Serrano, M., De Guzman, A., et al. (2013) · Journal of Lipid Research · doi:10.1194/jlr.m038869 · Cited by 319
Organoid cultures recapitulate esophageal adenocarcinoma heterogeneity providing a model for clonality studies and precision therapeutics
Li, X., Francies, H. E., Secrier, M., Perner, J., Miremadi, A., Galeano-Dalmau, N., Barendt, W. J., Letchford, L., Leyden, G. M., Goffin, E. K., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05190-9 · Cited by 316
Astrocytic abnormalities and global DNA methylation patterns in depression and suicide
Nagy, C., Suderman, M., Yang, J., Szyf, M., Mechawar, N., Ernst, C., & Turecki, G. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.21 · Cited by 301
Organoid Cultures as Preclinical Models of Non–Small Cell Lung Cancer
Shi, R., Radulovich, N., Ng, C., Liu, N., Notsuda, H., Cabanero, M., Martins-Filho, S. N., Raghavan, V., Li, Q., Mer, A. S., et al. (2020) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-19-1376 · Cited by 316
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Bergström, A., Frantz, L., Schmidt, R., Ersmark, E., Lebrasseur, O., Girdland-Flink, L., Lin, A. T., Storå, J., Sjögren, K.-G., Anthony, D., et al. (2020) · Science · doi:10.1126/science.aba9572 · Cited by 297
Genomic structure in Europeans dating back at least 36,200 years
Seguin-Orlando, A., Korneliussen, T. S., Sikora, M., Malaspinas, A.-S., Manica, A., Moltke, I., Albrechtsen, A., Ko, A., Margaryan, A., Moiseyev, V., et al. (2014) · Science · doi:10.1126/science.aaa0114 · Cited by 315
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Wand, M. E., Bock, L. J., Bonney, L. C., & Sutton, J. M. (2017) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.01162-16 · Cited by 313
Effect of predicted protein-truncating genetic variants on the human transcriptome
Rivas, M. A., Pirinen, M., Conrad, D. F., Lek, M., Tsang, E. K., Karczewski, K. J., Maller, J. B., Kukurba, K. R., DeLuca, D. S., Fromer, M., et al. (2015) · Science · doi:10.1126/science.1261877 · Cited by 313
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Pickrell, J. K., Pai, A. A., Gilad, Y., & Pritchard, J. K. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1001236 · Cited by 311
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Sun, W., Poschmann, J., Cruz-Herrera del Rosario, R., Parikshak, N. N., Hajan, H. S., Kumar, V., Ramasamy, R., Belgard, T. G., Elanggovan, B., Wong, C. C. Y., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.031 · Cited by 306
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Self-citation
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Cas9 activates the p53 pathway and selects for p53-inactivating mutations
Enache, O. M., Rendo, V., Abdusamad, M., Lam, D., Davison, D., Pal, S., Currimjee, N., Hess, J., Pantel, S., Nag, A., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0623-4 · Cited by 285
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Cheong, J.-G., Ravishankar, A., Sharma, S., Parkhurst, C. N., Grassmann, S. A., Wingert, C. K., Laurent, P., Ma, S., Paddock, L., Miranda, I. C., et al. (2023) · Cell · doi:10.1016/j.cell.2023.07.019 · Cited by 309
Racioethnic diversity in the dynamics of the vaginal microbiome during pregnancy
Serrano, M. G., Parikh, H. I., Brooks, J. P., Edwards, D. J., Arodz, T. J., Edupuganti, L., Huang, B., Girerd, P. H., Bokhari, Y. A., Bradley, S. P., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0465-8 · Cited by 300
The exomes of the NCI-60 panel: a genomic resource for cancer biology and systems pharmacology
Abaan, O. D., Polley, E. C., Davis, S. R., Zhu, Y. J., Bilke, S., Walker, R. L., Pineda, M., Gindin, Y., Jiang, Y., Reinhold, W. C., et al. (2013) · Cancer Research · doi:10.1158/0008-5472.can-12-3342 · Cited by 288
Cell lineage analysis in human brain using endogenous retroelements
Evrony, G. D., Lee, E., Mehta, B. K., Benjamini, Y., Johnson, R. M., Cai, X., Yang, L., Haseley, P., Lehmann, H. S., Park, P. J., et al. (2015) · Neuron · doi:10.1016/j.neuron.2014.12.028 · Cited by 269
Population-Based Resequencing of Experimentally Evolved Populations Reveals the Genetic Basis of Body Size Variation in Drosophila melanogaster
Turner, T. L., Stewart, A. D., Fields, A. T., Rice, W. R., & Tarone, A. M. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1001336 · Cited by 297
Epigenetic patterns in a complete human genome
Gershman, A., Sauria, M. E. G., Guitart, X., Vollger, M. R., Hook, P. W., Hoyt, S. J., Jain, M., Shumate, A., Razaghi, R., Koren, S., et al. (2022) · Science · doi:10.1126/science.abj5089 · Cited by 297
Evaluation of 16S rDNA-Based Community Profiling for Human Microbiome Research
Jumpstart Consortium Human Microbiome Project Data Generation Working Group (2012) · PLoS ONE · doi:10.1371/journal.pone.0039315 · Cited by 297
Integrated Omics of Metastatic Colorectal Cancer
Li, C., Sun, Y.-D., Yu, G.-Y., Cui, J.-R., Lou, Z., Zhang, H., Huang, Y., Bai, C.-G., Deng, L.-L., Liu, P., et al. (2020) · Cancer Cell · doi:10.1016/j.ccell.2020.08.002 · Cited by 297
BRCA locus-specific loss of heterozygosity in germline BRCA1 and BRCA2 carriers
Maxwell, K. N., Wubbenhorst, B., Wenz, B. M., De Sloover, D., Pluta, J., Emery, L., Barrett, A., Kraya, A. A., Anastopoulos, I. N., Yu, S., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00388-9 · Cited by 296
Specification of CNS macrophage subsets occurs postnatally in defined niches
Masuda, T., Amann, L., Monaco, G., Sankowski, R., Staszewski, O., Krueger, M., Del Gaudio, F., He, L., Paterson, N., Nent, E., et al. (2022) · Nature · doi:10.1038/s41586-022-04596-2 · Cited by 294
Mobile genes in the human microbiome are structured from global to individual scales
Brito, I. L., Yilmaz, S., Huang, K., Xu, L., Jupiter, S. D., Jenkins, A. P., Naisilisili, W., Tamminen, M., Smillie, C. S., Wortman, J. R., et al. (2016) · Nature · doi:10.1038/nature18927 · Cited by 288

Authors: Li, H., & Durbin, R.
Affiliations: Wellcome Sanger Institute (GB)
Corresponding author: Durbin, Richard
ORCID: Li, Heng
Durbin, Richard
Venue: Bioinformatics
Publisher: Oxford University Press (OUP)
Published: 2009-05-18
Volume: 25
Issue: 14
Pages: 1754-1760
ISSN: 1367-4803 (ISSN-L)
1367-4811
DOI: 10.1093/bioinformatics/btp324
PMC: PMC2705234
OpenAlex: W2103441770
Cited by: 58,607
References: 32
Citations by year: 2026: 3541 · 2025: 4985 · 2024: 5800 · 2023: 5335 · 2022: 5575 · 2021: 5916 · 2020: 5161 · 2019: 4192 · 2018: 3819 · 2017: 3299 · 2016: 2900 · 2015: 2520 · 2014: 2193 · 2013: 1586 · 2012: 1007
FWCI: 233.42
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by-nc
creativecommons.org/licenses/by-nc/2.0/uk/ (vor, 2694 d)
Locations: Bioinformatics (publishedVersion, cc-by-nc)
PubMed Central (publishedVersion, cc-by-nc)
PubMed (publishedVersion)
Funders: Wellcome Trust (077192/Z/05/Z)
Broad Institute
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Physical Sciences › Mathematics › Theoretical Computer Science › Algorithms and Data Compression
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
Keywords: short-read alignment, Burrows-Wheeler transform, BWA, gapped alignment, indels, backward search, variant calling, resequencing, human genome, DNA sequencing
MeSH terms: Algorithms, Software, Sequence Alignment, Sequence Analysis, DNA, Genomics

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Fast and accurate short read alignment with Burrows-Wheeler transform

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