Development of Computational Pipeline Software for Genome/Exome Analysis on the K Computer

Authors

  • Kento Aoyama Tokyo Institute of Technology; National Institute of Advanced Industrial Science and Technology
  • Masanori Kakuta Tokyo Institute of Technology
  • Yuri Matsuzaki Tokyo Institute of Technology
  • Takashi Ishida Tokyo Institute of Technology
  • Masahito Ohue Tokyo Institute of Technology
  • Yutaka Akiyama Tokyo Institute of Technology

DOI:

https://doi.org/10.14529/jsfi200102

Abstract

Pipeline software that comprise tool and application chains for specific data processing have found extensive utilization in the analysis of several data types, such as genome, in bioinformatics research. Recent trends in genome analysis require use of pipeline software for optimum utilization of computational resources, thereby facilitating efficient handling of large-scale biological data accumulated on a daily basis. However, use of pipeline software in bioinformatics tends to be problematic owing to their large memory and storage capacity requirements, increasing number of job submissions, and a wide range of software dependencies. This paper presents a massive parallel genome/exome analysis pipeline software that addresses these difficulties. Additionally, it can be executed on a large number of K computer nodes. The proposed pipeline incorporates workflow management functionality that performs effectively when considering the task-dependency graph of internal executions via extension of the dynamic task distribution framework. Performance results pertaining to the core pipeline functionality, obtained via evaluation experiments performed using an actual exome dataset, demonstrate good scalability when using over a thousand nodes. Additionally, this study proposes several approaches to resolve performance bottlenecks of a pipeline by considering the domain knowledge pertaining to internal pipeline executions as a major challenge facing pipeline parallelization. 

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Published

2020-04-14

How to Cite

Aoyama, K., Kakuta, M., Matsuzaki, Y., Ishida, T., Ohue, M., & Akiyama, Y. (2020). Development of Computational Pipeline Software for Genome/Exome Analysis on the K Computer. Supercomputing Frontiers and Innovations, 7(1), 37–54. https://doi.org/10.14529/jsfi200102

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