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This article is part of the supplement: Symposium of Computations in Bioinformatics and Bioscience (SCBB07)

Open Access Research

Application of the Linux cluster for exhaustive window haplotype analysis using the FBAT and Unphased programs

Hiroyuki Mishima14, Andrew C Lidral12 and Jun Ni3*

Author Affiliations

1 Dows Institute for Dental Research, College of Dentistry, University of Iowa, Iowa City, IA 52242, USA

2 Department of Orthodontics, College of Dentistry, University of Iowa, Iowa City, IA 52242, USA

3 Department of Radiology, Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA

4 Current address: Nagasaki University Global Center of Excellence Program; and Department of Human Genetics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Nagasaki 852-8523, Japan

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BMC Bioinformatics 2008, 9(Suppl 6):S10  doi:10.1186/1471-2105-9-S6-S10

Published: 28 May 2008

Abstract

Background

Genetic association studies have been used to map disease-causing genes. A newly introduced statistical method, called exhaustive haplotype association study, analyzes genetic information consisting of different numbers and combinations of DNA sequence variations along a chromosome. Such studies involve a large number of statistical calculations and subsequently high computing power. It is possible to develop parallel algorithms and codes to perform the calculations on a high performance computing (HPC) system. However, most existing commonly-used statistic packages for genetic studies are non-parallel versions. Alternatively, one may use the cutting-edge technology of grid computing and its packages to conduct non-parallel genetic statistical packages on a centralized HPC system or distributed computing systems. In this paper, we report the utilization of a queuing scheduler built on the Grid Engine and run on a Rocks Linux cluster for our genetic statistical studies.

Results

Analysis of both consecutive and combinational window haplotypes was conducted by the FBAT (Laird et al., 2000) and Unphased (Dudbridge, 2003) programs. The dataset consisted of 26 loci from 277 extended families (1484 persons). Using the Rocks Linux cluster with 22 compute-nodes, FBAT jobs performed about 14.4–15.9 times faster, while Unphased jobs performed 1.1–18.6 times faster compared to the accumulated computation duration.

Conclusion

Execution of exhaustive haplotype analysis using non-parallel software packages on a Linux-based system is an effective and efficient approach in terms of cost and performance.