Technology dictates algorithms: recent developments in read alignment
Aligning sequencing reads onto a reference is an essential step of the majority of genomic analysis pipelines. Computational algorithms for read alignment have evolved in accordance with technological advances, leading to today’s diverse array of alignment methods. We provide a systematic survey of...
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| Published in | Genome Biology Vol. 22; no. 1; p. 249 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
BioMed Central
26.08.2021
Springer Nature B.V BMC |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1474-760X 1474-7596 1474-760X |
| DOI | 10.1186/s13059-021-02443-7 |
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| Abstract | Aligning sequencing reads onto a reference is an essential step of the majority of genomic analysis pipelines. Computational algorithms for read alignment have evolved in accordance with technological advances, leading to today’s diverse array of alignment methods. We provide a systematic survey of algorithmic foundations and methodologies across 107 alignment methods, for both short and long reads. We provide a rigorous experimental evaluation of 11 read aligners to demonstrate the effect of these underlying algorithms on speed and efficiency of read alignment. We discuss how general alignment algorithms have been tailored to the specific needs of various domains in biology. |
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| AbstractList | Aligning sequencing reads onto a reference is an essential step of the majority of genomic analysis pipelines. Computational algorithms for read alignment have evolved in accordance with technological advances, leading to today’s diverse array of alignment methods. We provide a systematic survey of algorithmic foundations and methodologies across 107 alignment methods, for both short and long reads. We provide a rigorous experimental evaluation of 11 read aligners to demonstrate the effect of these underlying algorithms on speed and efficiency of read alignment. We discuss how general alignment algorithms have been tailored to the specific needs of various domains in biology. Aligning sequencing reads onto a reference is an essential step of the majority of genomic analysis pipelines. Computational algorithms for read alignment have evolved in accordance with technological advances, leading to today's diverse array of alignment methods. We provide a systematic survey of algorithmic foundations and methodologies across 107 alignment methods, for both short and long reads. We provide a rigorous experimental evaluation of 11 read aligners to demonstrate the effect of these underlying algorithms on speed and efficiency of read alignment. We discuss how general alignment algorithms have been tailored to the specific needs of various domains in biology.Aligning sequencing reads onto a reference is an essential step of the majority of genomic analysis pipelines. Computational algorithms for read alignment have evolved in accordance with technological advances, leading to today's diverse array of alignment methods. We provide a systematic survey of algorithmic foundations and methodologies across 107 alignment methods, for both short and long reads. We provide a rigorous experimental evaluation of 11 read aligners to demonstrate the effect of these underlying algorithms on speed and efficiency of read alignment. We discuss how general alignment algorithms have been tailored to the specific needs of various domains in biology. Abstract Aligning sequencing reads onto a reference is an essential step of the majority of genomic analysis pipelines. Computational algorithms for read alignment have evolved in accordance with technological advances, leading to today’s diverse array of alignment methods. We provide a systematic survey of algorithmic foundations and methodologies across 107 alignment methods, for both short and long reads. We provide a rigorous experimental evaluation of 11 read aligners to demonstrate the effect of these underlying algorithms on speed and efficiency of read alignment. We discuss how general alignment algorithms have been tailored to the specific needs of various domains in biology. |
| ArticleNumber | 249 |
| Author | Alkan, Can Xue, Victor Mangul, Serghei Balliu, Brunilda Koslicki, David Taraszka, Kodi Rotman, Jeremy Yang, Harry Taegyun Alser, Mohammed Singer, Benjamin D. Baykal, Pelin Icer Shi, Huwenbo Mutlu, Onur Knyazev, Sergey Skums, Pavel Zelikovsky, Alex Deshpande, Dhrithi |
| Author_xml | – sequence: 1 givenname: Mohammed surname: Alser fullname: Alser, Mohammed organization: Computer Science Department, ETH Zürich, Computer Engineering Department, Bilkent University, Information Technology and Electrical Engineering Department – sequence: 2 givenname: Jeremy surname: Rotman fullname: Rotman, Jeremy organization: Department of Computer Science, University of California Los Angeles – sequence: 3 givenname: Dhrithi surname: Deshpande fullname: Deshpande, Dhrithi organization: Department of Clinical Pharmacy, School of Pharmacy, University of Southern California – sequence: 4 givenname: Kodi surname: Taraszka fullname: Taraszka, Kodi organization: Department of Computer Science, University of California Los Angeles – sequence: 5 givenname: Huwenbo surname: Shi fullname: Shi, Huwenbo organization: Department of Epidemiology, Harvard T.H. Chan School of Public Health, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard – sequence: 6 givenname: Pelin Icer surname: Baykal fullname: Baykal, Pelin Icer organization: Department of Computer Science, Georgia State University – sequence: 7 givenname: Harry Taegyun surname: Yang fullname: Yang, Harry Taegyun organization: Department of Computer Science, University of California Los Angeles, Bioinformatics Interdepartmental Ph.D. Program, University of California Los Angeles – sequence: 8 givenname: Victor surname: Xue fullname: Xue, Victor organization: Department of Computer Science, University of California Los Angeles – sequence: 9 givenname: Sergey surname: Knyazev fullname: Knyazev, Sergey organization: Department of Computer Science, Georgia State University – sequence: 10 givenname: Benjamin D. surname: Singer fullname: Singer, Benjamin D. organization: Division of Pulmonary and Critical Care Medicine, Northwestern University Feinberg School of Medicine, Department of Biochemistry & Molecular Genetics, Northwestern University Feinberg School of Medicine, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine – sequence: 11 givenname: Brunilda surname: Balliu fullname: Balliu, Brunilda organization: Department of Computational Medicine, University of California Los Angeles – sequence: 12 givenname: David surname: Koslicki fullname: Koslicki, David organization: Computer Science and Engineering, Pennsylvania State University, Biology Department, Pennsylvania State University, The Huck Institutes of the Life Sciences, Pennsylvania State University – sequence: 13 givenname: Pavel surname: Skums fullname: Skums, Pavel organization: Department of Computer Science, Georgia State University – sequence: 14 givenname: Alex surname: Zelikovsky fullname: Zelikovsky, Alex organization: Department of Computer Science, Georgia State University, The Laboratory of Bioinformatics, I.M. Sechenov First Moscow State Medical University – sequence: 15 givenname: Can surname: Alkan fullname: Alkan, Can organization: Computer Engineering Department, Bilkent University, Bilkent-Hacettepe Health Sciences and Technologies Program – sequence: 16 givenname: Onur surname: Mutlu fullname: Mutlu, Onur organization: Computer Science Department, ETH Zürich, Computer Engineering Department, Bilkent University, Information Technology and Electrical Engineering Department – sequence: 17 givenname: Serghei orcidid: 0000-0003-4770-3443 surname: Mangul fullname: Mangul, Serghei email: serghei.mangul@gmail.com organization: Department of Clinical Pharmacy, School of Pharmacy, University of Southern California |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34446078$$D View this record in MEDLINE/PubMed |
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| Snippet | Aligning sequencing reads onto a reference is an essential step of the majority of genomic analysis pipelines. Computational algorithms for read alignment have... Abstract Aligning sequencing reads onto a reference is an essential step of the majority of genomic analysis pipelines. Computational algorithms for read... |
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| SubjectTerms | Accuracy Algorithms Animal Genetics and Genomics Bias Bioinformatics Biomedical and Life Sciences Computational Biology - methods Computer applications Evolutionary Biology genome Genome, Human Genomes Genomic analysis genomics HIV - physiology Human Genetics Humans Life Sciences Metagenomics Microbial Genetics and Genomics Plant Genetics and Genomics Review Sequence Alignment Sulfites surveys |
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| Title | Technology dictates algorithms: recent developments in read alignment |
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