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|Title:||Using and evolutionary algorithm and parallel computing for haplotyping in a general complex pedigree with multiple marker loci||Contributor(s):||Lee, Sang Hong (author); Van Der Werf, Julius Herman (author) ; Kinghorn, Brian (author)||Publication Date:||2008||DOI:||10.1186/1471-2105-9-189||Handle Link:||https://hdl.handle.net/1959.11/3854||Abstract:||Background: Haplotype reconstruction is important in linkage mapping and association mapping of quantitative trait loci (QTL). One widely used statistical approach for haplotype reconstruction is simulated annealing (SA), implemented in SimWalk2. However, the algorithm needs a very large number of sequential iterations, and it does not clearly show if convergence of the likelihood is obtained. Results: An evolutionary algorithm (EA) is a good alternative whose convergence can be easily assessed during the process. It is feasible to use a powerful parallel-computing strategy with the EA, increasing the computational efficiency. It is shown that the EA can be ~4 times faster and gives more reliable estimates than SimWalk2 when using 4 processors. In addition, jointly updating dependent variables can increase the computational efficiency up to ~2 times. Overall, the proposed method with 4 processors increases the computational efficiency up to ~8 times compared to SimWalk2. The efficiency will increase more with a larger number of processors. Conclusion: The use of the evolutionary algorithm and the joint updating method can be a promising tool for haplotype reconstruction in linkage and association mapping of QTL.||Publication Type:||Journal Article||Source of Publication:||BMC Bioinformatics, v.9 (189)||Publisher:||BioMed Central Ltd||Place of Publication:||United Kingdom||ISSN:||1471-2105||Fields of Research (FoR) 2008:||060412 Quantitative Genetics (incl Disease and Trait Mapping Genetics)||Socio-Economic Objective (SEO) 2008:||830310 Sheep - Meat||Peer Reviewed:||Yes||HERDC Category Description:||C1 Refereed Article in a Scholarly Journal|
|Appears in Collections:||Journal Article|
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