Using an evolutionary algorithm and parallel computing for haplotyping in a general complex pedigree with multiple marker loci.
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 approximately 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 approximately 2 times. Overall, the proposed method with 4 processors increases the computational efficiency up to approximately 8 times compared to SimWalk2. The efficiency will increase more with a larger number of processors.


CONCLUSIONS
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.
Lee
Sang Hong
SH
The Institute for Genetics and Bioinformatics, School of Environmental and Rural Science, University of New England, Armidale, New South Wales 2351, Australia. slee38@une.edu.au
Van der Werf
Julius H J
JH
Kinghorn
Brian P
BP
D000465:Algorithms; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D019143:Evolution, Molecular; D005819:Genetic Markers / Q000235:genetics*; D006239:Haplotypes / Q000235:genetics*; D008969:Molecular Sequence Data; D010375:Pedigree; D040641:Quantitative Trait Loci / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods; D017422:Sequence Analysis, DNA / Q000379:methods*
D005819:Genetic Markers