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 inGenome Biology Vol. 22; no. 1; p. 249
Main Authors Alser, Mohammed, Rotman, Jeremy, Deshpande, Dhrithi, Taraszka, Kodi, Shi, Huwenbo, Baykal, Pelin Icer, Yang, Harry Taegyun, Xue, Victor, Knyazev, Sergey, Singer, Benjamin D., Balliu, Brunilda, Koslicki, David, Skums, Pavel, Zelikovsky, Alex, Alkan, Can, Mutlu, Onur, Mangul, Serghei
Format Journal Article
LanguageEnglish
Published London BioMed Central 26.08.2021
Springer Nature B.V
BMC
Subjects
Online AccessGet full text
ISSN1474-760X
1474-7596
1474-760X
DOI10.1186/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.
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
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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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