Carlborg, Örjan
- Department of Animal Biosciences, Swedish University of Agricultural Sciences
Abstract
Here we describe a general method fur improving computational efficiency in simultaneous mapping of multiple interacting quantitative trait loci (QTL). The method uses a genetic algorithm to search fur QTL in the genome instead of an exhaustive enumerative ("step-by-step") search. It can be used together with any method of QTL, mapping based on a genomic search, since it only provides a more efficient way to search the genome for QTL. The computational demand decreases by a factor of similar to 130 when using genetic algorithm-based mapping instead of an exhaustive enumerative search for two QTL in a genome size of 2000 cM using a resolution of 1 cM. The advantage of using a genetic algorithm increases further for larger genomes, higher resolutions, and searches for more QTL. We show that a genetic algorithm-based search has efficiency higher than or equal to a search method conditioned on previously identified QTL fur all epistatic models tested and that this efficiency is comparable to that of all exhaustive search for multiple QTL. The genetic algorithm is thus a powerful and computationally tractable alternative to the exhaustive enumerative search for simultaneous mapping of multiple interacting QTL. The use of genetic algorithms for simultaneous mapping of more than two QTL and fur deter-mining empirical significance thresholds using permutation tests is also discussed.
Published in
Genetics
2000, volume: 155, number: 4, pages: 2003-2010
Publisher: GENETICS
SLU Authors
Andersson, Leif
- Department of Animal Biosciences, Swedish University of Agricultural Sciences
- Department of Animal Biosciences, Swedish University of Agricultural Sciences
UKÄ Subject classification
Genetics and Genomics
Publication identifier
- DOI: https://doi.org/10.1093/genetics/155.4.2003
Permanent link to this page (URI)
https://res.slu.se/id/publ/57927