ISCAS OpenIR
Parallel compression and decompression of DNA sequence reads in FASTQ format
Zheng, Jingjing (1); Wang, Ting (1)
2014
SourceInternational Journal of Hybrid Information Technology
ISSN17389968
Volume7Issue:4Pages:91-100
English AbstractLarge volumes of short reads of genomic data are generated by high-throughput sequencing instruments. The FASTQ format is widely accepted as the input format of genomic reads and has presented challenges in data storage, management, and transfer. The performance of this type of serial algorithms such as G-SQZ and DSRC is limited by the single processor and the memory in a single computer. Utilizing data parallelism, the circular dual queues of buffers, memory mapping integrated with superblocks, pipeline parallelism with multi threads, and so on, we present the parallel compression and decompression methods for DNA sequence reads in FASTQ format based on the parallel computer architectures of the cluster and the SMP. Experimental results for the parallel DSRC algorithm clearly show the efficiency of using the powerful computing resources from multi computing nodes and multi cores of each node. The speedups vary from 46 to 62 for parallel compression and vary from 40 to 58 for parallel decompression by using 10 nodes of the cluster in Tianhe-1A super computer. Test results on the SMP machine are also pleasant. The methods could be applied to any serial compressing algorithms of DNA sequence reads in FASTQ format only if they have the traits of index and superblocks. © 2014 SERSC.; Large volumes of short reads of genomic data are generated by high-throughput sequencing instruments. The FASTQ format is widely accepted as the input format of genomic reads and has presented challenges in data storage, management, and transfer. The performance of this type of serial algorithms such as G-SQZ and DSRC is limited by the single processor and the memory in a single computer. Utilizing data parallelism, the circular dual queues of buffers, memory mapping integrated with superblocks, pipeline parallelism with multi threads, and so on, we present the parallel compression and decompression methods for DNA sequence reads in FASTQ format based on the parallel computer architectures of the cluster and the SMP. Experimental results for the parallel DSRC algorithm clearly show the efficiency of using the powerful computing resources from multi computing nodes and multi cores of each node. The speedups vary from 46 to 62 for parallel compression and vary from 40 to 58 for parallel decompression by using 10 nodes of the cluster in Tianhe-1A super computer. Test results on the SMP machine are also pleasant. The methods could be applied to any serial compressing algorithms of DNA sequence reads in FASTQ format only if they have the traits of index and superblocks. © 2014 SERSC.
Indexed TypeEI
Department(1) Parallel Software and Computational Science Lab, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China; (2) Research Center of Parallel Software Cloud Application, Institute of Software Application Technology, Guangzhou and Chinese Academy of Sciences, Guangzhou 511458, China
Language英语
Content Type期刊论文
URIhttp://ir.iscas.ac.cn/handle/311060/17026
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Zheng, Jingjing ,Wang, Ting . Parallel compression and decompression of DNA sequence reads in FASTQ format[J]. International Journal of Hybrid Information Technology,2014,7(4):91-100.
APA Zheng, Jingjing ,&Wang, Ting .(2014).Parallel compression and decompression of DNA sequence reads in FASTQ format.International Journal of Hybrid Information Technology,7(4),91-100.
MLA Zheng, Jingjing ,et al."Parallel compression and decompression of DNA sequence reads in FASTQ format".International Journal of Hybrid Information Technology 7.4(2014):91-100.
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