Presentation 2014/6/18
Large-scale Parallelization of Exome Analysis Pipeline on K-computer
KENTO AOYAMA, MASANORI KAKUTA, YURI MATSUZAKI, TAKASHI ISHIDA, YUTAKA AKIYAMA,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) Exome analysis, which is a method to analyze only protein coding region, has been used in various research fields such as a cancer genome research. Because of the improvement of a high-speed sequencer, demands of effective sequence analysis on large computational environment have been increased. Genomon-exome is a useful pipeline software for analyzing exome data but executable on only general PC clusters. In this study, We attempted to implement the Genomon-exome on the K-computer using a Master-Worker model task distribution framework implemented MPI. We also evaluated the scalability of the pipeline on K-computer.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) K-computer / Exome analysis / Pipeline / Genomon-exome / MPI
Paper # Vol.2014-MPS-98 No.33,Vol.2014-BIO-38 No.33
Date of Issue

Conference Information
Committee IBISML
Conference Date 2014/6/18(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Information-Based Induction Sciences and Machine Learning (IBISML)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Large-scale Parallelization of Exome Analysis Pipeline on K-computer
Sub Title (in English)
Keyword(1) K-computer
Keyword(2) Exome analysis
Keyword(3) Pipeline
Keyword(4) Genomon-exome
Keyword(5) MPI
1st Author's Name KENTO AOYAMA
1st Author's Affiliation Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology:Education Academy of Computational Life Sciences, Tokyo Institute of Technology()
2nd Author's Name MASANORI KAKUTA
2nd Author's Affiliation Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology
3rd Author's Name YURI MATSUZAKI
3rd Author's Affiliation Education Academy of Computational Life Sciences, Tokyo Institute of Technology
4th Author's Name TAKASHI ISHIDA
4th Author's Affiliation Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology
5th Author's Name YUTAKA AKIYAMA
5th Author's Affiliation Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology:Education Academy of Computational Life Sciences, Tokyo Institute of Technology
Date 2014/6/18
Paper # Vol.2014-MPS-98 No.33,Vol.2014-BIO-38 No.33
Volume (vol) vol.114
Number (no) 105
Page pp.pp.-
#Pages 7
Date of Issue