ArticleSource code for biology and medicine2010
ParaHaplo 2.0: a program package for haplotype-estimation and haplotype-based whole-genome association study using parallel computing.
Article in Source code for biology and medicine, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- ParaHaplo 3.0: A program package for imputation and a haplotype-based whole-genome association study using hybrid parallel computing.Source code for biology and medicine · 2011Article
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2 authors.
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Abstract
backgroundThe use of haplotype-based association tests can improve the power of genome-wide association studies. Since the observed genotypes are unordered pairs of alleles, haplotype phase must be inferred. However, estimating haplotype phase is time consuming. When millions of single-nucleotide polymorphisms (SNPs) are analyzed in genome-wide association study, faster methods for haplotype estimation are required.
methodsWe developed a program package for parallel computation of haplotype estimation. Our program package, ParaHaplo 2.0, is intended for use in workstation clusters using the Intel Message Passing Interface (MPI). We compared the performance of our algorithm to that of the regular permutation test on both Japanese in Tokyo, Japan and Han Chinese in Beijing, China of the HapMap dataset.
resultsParallel version of ParaHaplo 2.0 can estimate haplotypes 100 times faster than a non-parallel version of the ParaHaplo.
conclusionParaHaplo 2.0 is an invaluable tool for conducting haplotype-based genome-wide association studies (GWAS). The need for fast haplotype estimation using parallel computing will become increasingly important as the data sizes of such projects continue to increase. The executable binaries and program sources of ParaHaplo are available at the following address: http://en.sourceforge.jp/projects/parallelgwas/releases/
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