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Comparisons of four approximation algorithms for large-scale linkage map construction


Efficient construction of large-scale linkage maps is highly desired in current gene mapping projects. To evaluate the performance of available approaches in the literature, four published methods, the insertion (IN), seriation (SER), neighbor mapping (NM), and unidirectional growth (UG) were compared on the basis of simulated F2 data with various population sizes, interferences, missing genotype rates, and mis-genotyping rates. Simulation results showed that the IN method outperformed, or at least was comparable to, the other three methods. These algorithms were also applied to a real data set and results showed that the linkage order obtained by the IN algorithm was superior to the other methods. Thus, this study suggests that the IN method should be used when constructing large-scale linkage maps.

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This study was supported in part by the Mississippi Agricultural and Forestry Experiment Station, Mississippi State University and the Agricultural Experiment Station of South Dakota State University, and by the National Institutes of Health Grant R01DA025095. The authors would like to appreciate Drs. David Fang and Michael Gonda for their helpful comments. We also want to express our great appreciations for the editor and three anonymous reviewers for their critical and helpful comments that greatly improved the quality of this paper.

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Correspondence to Jixiang Wu.

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Approved for publication as Journal Article No. J-11828 of the Mississippi Agricultural and Forestry Experiment Station, Mississippi State University. Mention of trademark, proprietary products, or vendor does not constitute a guarantee or warranty of the product by USDA nor any other participating institution and does not imply its approval to the exclusion of other products or vendors that may also be suitable.

Communicated by M. Sillanpaa.

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Wu, J., Jenkins, J.N., McCarty, J.C. et al. Comparisons of four approximation algorithms for large-scale linkage map construction. Theor Appl Genet 123, 649–655 (2011).

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  • Recombination Frequency
  • Neighbor Mapping
  • Insertion Method
  • Linkage Algorithm
  • Crossover Interference