Genetic mapping and genomic selection using recombination breakpoint data.

ABSTRACT: The correct models for quantitative trait locus mapping are the ones that simultaneously include all significant genetic effects. Such models are difficult to handle for high marker density. Improving statistical methods for high-dimensional data appears to have reached a plateau. Alternative approaches must be explored to break the bottleneck of genomic data analysis. The fact that all markers are located in a few chromosomes of the genome leads to linkage disequilibrium among markers. This suggests that dimension reduction can also be achieved through data manipulation. High-density markers are used to infer recombination breakpoints, which then facilitate construction of bins. The bins are treated as new synthetic markers. The number of bins is always a manageable number, on the order o

SUBMITTER: Xu S 

PROVIDER: S-EPMC3813840 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature