The DOI matches its Crossref record; 73 of the 74 references it cites were found in a registry or an index.
A survey of sequence alignment algorithms for next-generation sequencing
Open accessAbstract
Rapidly evolving sequencing technologies produce data on an unparalleled scale. A central challenge to the analysis of this data is sequence alignment, whereby sequence reads must be compared to a reference. A wide variety of alignment algorithms and software have been subsequently developed over the past two years. In this article, we will systematically review the current development of these algorithms and introduce their practical applications on different types of experimental data. We come to the conclusion that short-read alignment is no longer the bottleneck of data analyses. We also consider future development of alignment algorithms with respect to emerging long sequence reads and the prospect of cloud computing.
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“When we examined the inter-site DEG false positive rates for several other analysis pipelines (WHAM34, Mapsplice35, Novoalign36, Cufflinks23, 37, 38 and HTSeq39) we found similarly high false positive rates, regardless of the analysis pipeline or read alignment methods used (Supplementary Fig. 1).”
From Detecting and correcting systematic variation in large-scale RNA sequencing data (2014) · cites this paper as [36]
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Cites
Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669
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-citationFast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
Self-citationUltrafast 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
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
Fast and accurate long-read alignment with Burrows-Wheeler transform.
Li, H., & Durbin, R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp698 · Cited by 12,063
Self-citationTopHat: discovering splice junctions with RNA-Seq
Trapnell, C., Pachter, L. S., & Salzberg, S. L. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp120 · Cited by 11,682
Identification of common molecular subsequences
Smith, T. F., & Waterman, M. S. (1981) · Journal of Molecular Biology · doi:10.1016/0022-2836(81)90087-5 · Cited by 9,962
<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
Research works printed but not linked: 1
- 1985, THEORETICAL COMPUTER SCIENCE, 40, 31
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Trimmomatic: a flexible trimmer for Illumina sequence data
Bolger, A. M., Lohse, M., & Usadel, B. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu170 · Cited by 65,548
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote
Liao, Y., Smyth, G. K., & Shi, W. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt214 · Cited by 3,064
Adaptive seeds tame genomic sequence comparisonPreprint
Kiełbasa, S. M., Wan, R., Sato, K., Horton, P., & Frith, M. C. (2011) · Genome Research · doi:10.1101/gr.113985.110 · Cited by 1,287
The Ensembl gene annotation system
Aken, B. L., Ayling, S., Barrell, D., Clarke, L., Curwen, V., Fairley, S., Fernandez Banet, J., Billis, K., García Girón, C., Hourlier, T., et al. (2016) · Database · doi:10.1093/database/baw093 · Cited by 1,086
Metadata
- Authors
- Li, H., & Homer, N.
- Affiliations
- Broad Institute (US)
- ORCID
- Li, H.
- Venue
- Briefings in Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-05-11
- Volume
- 11
- Issue
- 5
- Pages
- 473-483
- ISSN
- 1467-5463 (ISSN-L)
- 1477-4054
- PMC
- PMC2943993
- OpenAlex
- W2093931624
- Cited by
- 875
- References
- 74
- Citations by year
- 2026: 11 · 2025: 21 · 2024: 22 · 2023: 21 · 2022: 20 · 2021: 37 · 2020: 41 · 2019: 41 · 2018: 69 · 2017: 52 · 2016: 74 · 2015: 88 · 2014: 118 · 2013: 105 · 2012: 83
- FWCI
- 7.25
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Briefings in Bioinformatics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Human Genome Research Institute (U01HG005210, U01HG005208)
- 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
- sequence alignment, next-generation sequencing, short-read alignment, long-read sequencing, alignment algorithms, reference genome mapping, cloud computing, bioinformatics software
- MeSH terms
- Algorithms, Base Sequence, Humans, Software, Genome, Human, Sequence Alignment, Sequence Analysis, DNA
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