Optimization for Detection of Somatic Mutations Based on MuTect 


Vol. 44,  No. 5, pp. 1024-1031, May  2019
10.7840/kics.2019.44.5.1024


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  Abstract

Techniques for detecting somatic mutations, which examine the causes of various diseases, especially the causes of tumor from genome data, play an important role in genome data analysis. In this paper, we investigated MuTect, one of the popular tools for detecting somatic mutations, and analyzed causes of its slow execution speed. This is due to inefficiency of MuTect algorithm where Pileup operator is executed redundantly and processing results of the operator is also duplicated. Thus, in order to solve the inefficiency, we devised a method called data rearrangement that changes data structure of genome data loaded on memory and implemented an optimized MuTect. We conducted experiments for real genome data, and showed that our optimized MuTect greatly improves the slow execution speed of MuTect without degradation of detection performance.

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  Cite this article

[IEEE Style]

B. Na and S. Yoon, "Optimization for Detection of Somatic Mutations Based on MuTect," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 5, pp. 1024-1031, 2019. DOI: 10.7840/kics.2019.44.5.1024.

[ACM Style]

Byunggook Na and Sungroh Yoon. 2019. Optimization for Detection of Somatic Mutations Based on MuTect. The Journal of Korean Institute of Communications and Information Sciences, 44, 5, (2019), 1024-1031. DOI: 10.7840/kics.2019.44.5.1024.

[KICS Style]

Byunggook Na and Sungroh Yoon, "Optimization for Detection of Somatic Mutations Based on MuTect," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 5, pp. 1024-1031, 5. 2019. (https://doi.org/10.7840/kics.2019.44.5.1024)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880