Journal of Jilin University Science Edition

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Algorithms for Detecting GeneGene Interactions Based on Cloud Platform

LIU Guixia, LI Guangli, LI Han   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2014-03-10 Online:2014-05-26 Published:2014-08-27
  • Contact: LI Guangli E-mail:calculatinggod@foxmail.com

Abstract:

The authors proposed an optimized algorithm for detecting genegene interactions based on MapReduce model, namely, MRANOVA.Compared with the traditional FastANOVA algorithm, this algorithm puts forward the concept of parallel processing during which an efficient parallel computing model is used. This improvement can make the problem of high computational complexities with the largescale data of the existing algorithms solved. Analyzing
results of the experiment, we can draw the following conclusion: MRANOVA algorithm can make the best use of the promising power of parallelism computation of the cloud platform. As the scale of the data becomes larger, the speedup is more close to the number of clusters. Thus, this optimized algorithm can detect epistatic interaction more efficiently.

Key words: genegene interaction, MapReduce model, cloud computing

CLC Number: 

  • TP311.1