Abstract
MS-Alignment is an unrestrictive post-translational modification (PTM) search algorithm with an advantage of searching for all types of PTMs at once in a blind mode. However, it is time-consuming, and thus it could not well meet the challenge of large-scale protein database and spectra. We use Graphic Processor Unit (GPU) to accelerate MS-Alignment for reducing identification time to meet time requirement. The work mainly includes two parts. (1) The step of Database search and Candidate generation (DC) consumes most of the time in MS-Alignment. We propose an algorithm of DC on GPU based on CUDA (DCGPU). The data parallelism way is partitioning protein sequences. We adopt several methods to optimize DCGPU implementation. (2) For further acceleration, we propose an algorithm of MS-Alignment on GPU cluster based on MPI and CUDA (MC_MS-A). The comparison experiments show that the average speedup ratio could be above 26 in the model of at most one modification and above 41 in the model of at most two modifications. The experimental results show that MC_MS-A on GPU Cluster could reduce the time of identifying 31173 spectra from about 2.853 months predicted to 0.606 h. Accelerating MS-Alignment on GPU is applicable for large-scale data requiring for high-speed processing.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ari MF (2008) Algorithms for tandem mass spectrometry-based proteomics. Ph.D. thesis, University of California, San Diego
David K, Hwu W-M (2010) ECE 498AL: Applied Parallel Programming. http://courses.ece.illinois.edu/ece498/al/
Dekel T, Stephen T, Ebrahim Z et al (2005) Identification of post-translational modifications via blind search of mass-spectra. Nat Biotechnol 23:1562–1567
John DO, David L, Naga G et al (2007) A survey of general-purpose computation on graphics hardware. Comput Graph Forum 26:80–113
Liu Y, Douglas LM, Bertil S (2009) CUDASW++: optimizing Smith-Waterman sequence database searched for CUDA-enabled graphics processing units. BMC Res Notes 2:73
Lukasz L, Witold R (2009) An efficient implementation of Smith-Waterman algorithm on GPU using CUDA, for massively parallel scanning of sequence databases. In: 2009 IEEE international symposium on parallel and distributed processing, pp 1–8
Michael CS, Cole T, Arthur LD et al (2007) High-throughput sequence alignment using graphics processing units. BMC Bioinformatics 8:474
NVIDIA Corporation (2009) NVIDIA CUDA Programming Guide Version 2.3.1. http://www.nvidia.cn/object/cuda_get_cn.html
Sain-Zee U, Melvin L, Sara SB et al (2008) CUDA-Lite: reducing GPU programming complexity. In: Languages and compilers for parallel computing: 21th international workshop (LCPC), 2008, pp 1–15
Seungjin N, Jaeho J, Heejin P et al (2008) Unrestrictive identification of multiple post-translational modifications from tandem mass spectrometry using an error-tolerant algorithm based on an extended sequence tag approach. Mol Cell Proteomics 7:2452–2463
Sheng Q, Xie T, Ding D (2000) De novo interpretation of MS/MS spectra and protein identification via database searching (in Chinese). Acta Biochim Biophys Sin 32:595–600
Stephen T, Shu H, Ari F et al (2005) Inspect: fast and accurate identification of post-translationally modified peptides from tandem mass spectra. Anal Chem 77:4626–4639
Svetlin AM, Giorgio V (2008) CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment. BMC Bioinform 9:S10
Tu Q (2009) Research on parallelization and optimization of protein post-translational modifications software InsPecT (in Chinese). Master thesis, Computer Network Information Center of Chinese Academy of Sciences
Wu E (2004) State of the art and future challenge on general purpose computation by graphics processing unit (in Chinese). J Softw 15:1493–1504
Zhai Y (2010) Research and implementation of using GPU to accelerate MS-alignment for identification of post-translational modifications (in Chinese). Master Thesis, Computer Network Information Center of Chinese Academy of Sciences
Zhai Y, Tu Q, Lang X et al (2010a) Research of CUDA-based acceleration of MS-alignment for identification of post-translational modifications (in Chinese). Appl Res Comput 27:3409–3414
Zhai Y, Tu Q, Lang X et al (2010b) Research of using GPU to accelerate MS-alignment algorithm to identify protein post-translational modifications (in Chinese). J Comput Res Dev (in review)
Zhang S, Yanli C (2009) CUDA of GPU high performance computing (in Chinese). China WaterPower Press, Beijing
Acknowledgments
This work was supported by CAS grant KGGX1-YW-13 and Computer Network Information Center of CAS grant CNIC_ZR_09005. We are grateful to Professor Wu Jiarui of SIBS for directing our research work and to PhD Sheng Quanhu for providing mass spectra and protein databases. This research was supported in part by the National High Technology Research and Development Program of China 2006AA01A116 and Major Research Equipment Development Project of Ministry of Finance ZDYZ2008-2. The protein databases of ipi.ARATH.v3.51, ipi.HUMAN.v3.53 and uniprot_sprot were downloaded at EMBL-EBI website.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Yantang, Z., Qiang, T., Xianyu, L., Zhonghua, L., Xuebin, C. (2013). Research of Acceleration MS-Alignment Identifying Post-Translational Modifications on GPU. In: Yuen, D., Wang, L., Chi, X., Johnsson, L., Ge, W., Shi, Y. (eds) GPU Solutions to Multi-scale Problems in Science and Engineering. Lecture Notes in Earth System Sciences. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16405-7_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-16405-7_13
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16404-0
Online ISBN: 978-3-642-16405-7
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)