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Technology dictates algorithms: recent developments in read alignment

delete2021-08-26
delete64
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OA
AI
M
Mohammed Alser
J
Jeremy Rotman
D
Deshpande, Dhrithi
K
Kodi Taraszka
H
Huwenbo Shi
P
Pelin Icer Baykal
H
Harry Yang
V
Victor Xue
S
Sergey Knyazev
B
Benjamin D. Singer
B
Brunilda Balliu
D
David Koslicki
P
Pavel Skums
A
Alex Zelikovsky
C
Can Alkan
O
Onur Mutlu
S
Serghei Mangul *
DOI:10.1186/s13059-021-02443-7delete
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Abstract

Abstract

En 中文
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.
Keywords:
MULTIPLE SEQUENCE ALIGNMENT
SPLICE JUNCTIONS
GENOME ASSEMBLIES
LOCAL ALIGNMENT
DNA METHYLATION
LONG READS
RNA
GENERATION
ACCURATE
EFFICIENT
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Journal

G
Genome Biology
IF:
9.4
Papers:
6.4K
Citations:
7.3W

Organization

U
university of southern california
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4.7W
Papers: 3.8W
Citations: 51
H
Harvard T.H. Chan School of Public Health
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1.6W
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B
Broad Institute
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U
university system of georgia
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7.3W
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ETH Zurich
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3.0W
Papers: 2.4W
Citations: 8.4W
S
swiss federal institutes of technology domain
Scholars:
9.0W
Papers: 8.0W
Citations: 163
University of California System cover
University of California System
Scholars:
37.7W
Papers: 33.8W
Citations: 6.6K
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