A novel method for estimating linkage maps.
The goal of linkage mapping is to find the true order of loci from a chromosome. Since the number of possible orders is large even for a modest number of loci, the problem of finding the optimal solution is known as a NP-hard problem or traveling salesman problem (TSP). Although a number of algorithms are available, many either are low in the accuracy of recovering the true order of loci or require tremendous amounts of computational resources, thus making them difficult to use for reconstructing a large-scale map. We developed in this article a novel method called unidirectional growth (UG) to help solve this problem. The UG algorithm sequentially constructs the linkage map on the basis of novel results about additive distance. It not only is fast but also has a very high accuracy in recovering the true order of loci according to our simulation studies. Since the UG method requires n-1 cycles to estimate the ordering of n loci, it is particularly useful for estimating linkage maps consisting of hundreds or even thousands of linked codominant loci on a chromosome.
Tan
Yuan-De
YD
Human Genetics Center, School of Public Health, University of Texas, Houston 77030, USA.
Fu
Yun-Xin
YX
D000465:Algorithms; D002874:Chromosome Mapping / Q000379:methods; D002875:Chromosomes / Q000235:genetics*; D003198:Computer Simulation; D005799:Genes, Dominant / Q000235:genetics; D008040:Genetic Linkage; D008957:Models, Genetic; D040641:Quantitative Trait Loci / Q000235:genetics*