MP-LAMP: Parallel detection of statistically significant multi-loci markers on cloud platforms

Kazuki Yoshizoe, Aika Terada, Koji Tsuda

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


Summary: Exhaustive detection of multi-loci markers from genome-wide association study datasets is a computationally challenging problem. This paper presents a massively parallel algorithm for finding all significant combinations of alleles and introduces a software tool termed MP-LAMP that can be easily deployed in a cloud platform, such as Amazon Web Service, as well as in an inhouse computer cluster. Multi-loci marker detection is an unbalanced tree search problem that cannot be parallelized by simple tree-splitting using generic parallel programming frameworks, such as Map-Reduce. We employ work stealing and periodic reduce-broadcast to decrease the running time almost linearly to the number of cores.

Original languageEnglish
Pages (from-to)3047-3049
Number of pages3
Issue number17
Publication statusPublished - Sept 1 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics


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