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A Review on Sequence Alignment Algorithms for Short Reads Based on Next-Generation Sequencing
- Source :
- IEEE Access, Vol 8, Pp 189811-189822 (2020)
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- With recent advances in next-generation sequencing (NGS) technology, large volumes of data have been produced in the form of short reads. Sequence assembly involves using initial short reads to produce progressively longer contigs, and then using scaffolds to produce the final sequence. These processes each require evaluation of the extent of homology between different sequences. However, because the NGS platforms currently being developed are diverse, and the data being produced are of different sizes and read lengths, numerous algorithms are being developed with unique methodologies to process this complex data. It is difficult for biologists to manipulate the different features involved in these algorithms. Therefore, to reduce experimental trial-and-error, different strategies are required depending on the performance and purpose of the optimal algorithm, thereby facilitating understanding of algorithm methodologies and effective use of their various features. This study is a review of the different short read alignment algorithms and NGS platforms that have been developed to date, in order to aid efficient selection of algorithms for reference sequences and mapping of DNA data.
- Subjects :
- 0303 health sciences
General Computer Science
Contig
Computer science
0206 medical engineering
General Engineering
Sequence assembly
Sequence alignment
02 engineering and technology
DNA sequencing
hashing
03 medical and health sciences
chemistry.chemical_compound
chemistry
NGS
sequence alignment
read alignment
General Materials Science
lcsh:Electrical engineering. Electronics. Nuclear engineering
Algorithm
FM-index
lcsh:TK1-9971
020602 bioinformatics
DNA
030304 developmental biology
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....59a269bd8807f117f9a44fd5c02bf423