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

Yoshizoe, Kazuki; Terada, Aika; Tsuda, Koji · Bioinformatics · 2018

basic_science · Level V

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Abstract

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 in-house 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. MP-LAMP is available at https://github.com/tsudalab/mp-lamp. Supplementary data are available at Bioinformatics online.

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