Source Code for Biology and Medicine


Open Access Software review

ParaHaplo 3.0: A program package for imputation and a haplotype-based whole-genome association study using hybrid parallel computing

Kazuharu Misawa1* and Naoyuki Kamatani2

Author Affiliations

1 Research Program for Computational Science, Research and Development Group for Next-Generation Integrated Living Matter Simulation, and Fusion of Data and Analysis Research and Development Team, RIKEN, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan

2 Laboratory for Statistical Analysis, RIKEN Center for Genomic Medicine, Tokyo, Japan

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Source Code for Biology and Medicine 2011, 6:10 doi:10.1186/1751-0473-6-10

Published: 24 May 2011

Abstract

Background

Use of missing genotype imputations and haplotype reconstructions are valuable in genome-wide association studies (GWASs). By modeling the patterns of linkage disequilibrium in a reference panel, genotypes not directly measured in the study samples can be imputed and used for GWASs. Since millions of single nucleotide polymorphisms need to be imputed in a GWAS, faster methods for genotype imputation and haplotype reconstruction are required.

Results

We developed a program package for parallel computation of genotype imputation and haplotype reconstruction. Our program package, ParaHaplo 3.0, is intended for use in workstation clusters using the Intel Message Passing Interface. We compared the performance of ParaHaplo 3.0 on the Japanese in Tokyo, Japan and Han Chinese in Beijing, and Chinese in the HapMap dataset. A parallel version of ParaHaplo 3.0 can conduct genotype imputation 20 times faster than a non-parallel version of ParaHaplo.

Conclusions

ParaHaplo 3.0 is an invaluable tool for conducting haplotype-based GWASs. The need for faster genotype imputation and haplotype reconstruction using parallel computing will become increasingly important as the data sizes of such projects continue to increase. ParaHaplo executable binaries and program sources are available at http://en.sourceforge.jp/projects/parallelgwas/releases/ webcite.

Keywords:
ParaHaplo; haplotype reconstruction; genotype imputation; parallel computing; HapMap; GWAS