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A hybrid short read mapping accelerator

BACKGROUND: The rapid growth of short read datasets poses a new challenge to the short read mapping problem in terms of sensitivity and execution speed. Existing methods often use a restrictive error model for computing the alignments to improve speed, whereas more flexible error models are generall...

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Detalles Bibliográficos
Autores principales: Chen, Yupeng, Schmidt, Bertil, Maskell, Douglas L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3598928/
https://www.ncbi.nlm.nih.gov/pubmed/23441908
http://dx.doi.org/10.1186/1471-2105-14-67
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author Chen, Yupeng
Schmidt, Bertil
Maskell, Douglas L
author_facet Chen, Yupeng
Schmidt, Bertil
Maskell, Douglas L
author_sort Chen, Yupeng
collection PubMed
description BACKGROUND: The rapid growth of short read datasets poses a new challenge to the short read mapping problem in terms of sensitivity and execution speed. Existing methods often use a restrictive error model for computing the alignments to improve speed, whereas more flexible error models are generally too slow for large-scale applications. A number of short read mapping software tools have been proposed. However, designs based on hardware are relatively rare. Field programmable gate arrays (FPGAs) have been successfully used in a number of specific application areas, such as the DSP and communications domains due to their outstanding parallel data processing capabilities, making them a competitive platform to solve problems that are “inherently parallel”. RESULTS: We present a hybrid system for short read mapping utilizing both FPGA-based hardware and CPU-based software. The computation intensive alignment and the seed generation operations are mapped onto an FPGA. We present a computationally efficient, parallel block-wise alignment structure (Align Core) to approximate the conventional dynamic programming algorithm. The performance is compared to the multi-threaded CPU-based GASSST and BWA software implementations. For single-end alignment, our hybrid system achieves faster processing speed than GASSST (with a similar sensitivity) and BWA (with a higher sensitivity); for pair-end alignment, our design achieves a slightly worse sensitivity than that of BWA but has a higher processing speed. CONCLUSIONS: This paper shows that our hybrid system can effectively accelerate the mapping of short reads to a reference genome based on the seed-and-extend approach. The performance comparison to the GASSST and BWA software implementations under different conditions shows that our hybrid design achieves a high degree of sensitivity and requires less overall execution time with only modest FPGA resource utilization. Our hybrid system design also shows that the performance bottleneck for the short read mapping problem can be changed from the alignment stage to the seed generation stage, which provides an additional requirement for the future development of short read aligners.
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spelling pubmed-35989282013-03-29 A hybrid short read mapping accelerator Chen, Yupeng Schmidt, Bertil Maskell, Douglas L BMC Bioinformatics Methodology Article BACKGROUND: The rapid growth of short read datasets poses a new challenge to the short read mapping problem in terms of sensitivity and execution speed. Existing methods often use a restrictive error model for computing the alignments to improve speed, whereas more flexible error models are generally too slow for large-scale applications. A number of short read mapping software tools have been proposed. However, designs based on hardware are relatively rare. Field programmable gate arrays (FPGAs) have been successfully used in a number of specific application areas, such as the DSP and communications domains due to their outstanding parallel data processing capabilities, making them a competitive platform to solve problems that are “inherently parallel”. RESULTS: We present a hybrid system for short read mapping utilizing both FPGA-based hardware and CPU-based software. The computation intensive alignment and the seed generation operations are mapped onto an FPGA. We present a computationally efficient, parallel block-wise alignment structure (Align Core) to approximate the conventional dynamic programming algorithm. The performance is compared to the multi-threaded CPU-based GASSST and BWA software implementations. For single-end alignment, our hybrid system achieves faster processing speed than GASSST (with a similar sensitivity) and BWA (with a higher sensitivity); for pair-end alignment, our design achieves a slightly worse sensitivity than that of BWA but has a higher processing speed. CONCLUSIONS: This paper shows that our hybrid system can effectively accelerate the mapping of short reads to a reference genome based on the seed-and-extend approach. The performance comparison to the GASSST and BWA software implementations under different conditions shows that our hybrid design achieves a high degree of sensitivity and requires less overall execution time with only modest FPGA resource utilization. Our hybrid system design also shows that the performance bottleneck for the short read mapping problem can be changed from the alignment stage to the seed generation stage, which provides an additional requirement for the future development of short read aligners. BioMed Central 2013-02-26 /pmc/articles/PMC3598928/ /pubmed/23441908 http://dx.doi.org/10.1186/1471-2105-14-67 Text en Copyright ©2013 Chen et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Chen, Yupeng
Schmidt, Bertil
Maskell, Douglas L
A hybrid short read mapping accelerator
title A hybrid short read mapping accelerator
title_full A hybrid short read mapping accelerator
title_fullStr A hybrid short read mapping accelerator
title_full_unstemmed A hybrid short read mapping accelerator
title_short A hybrid short read mapping accelerator
title_sort hybrid short read mapping accelerator
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3598928/
https://www.ncbi.nlm.nih.gov/pubmed/23441908
http://dx.doi.org/10.1186/1471-2105-14-67
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