An efficient resampling method for assessing genome-wide statistical significance in mapping quantitative trait Loci.
Assessing genome-wide statistical significance is an important and difficult problem in multipoint linkage analysis. Due to multiple tests on the same genome, the usual pointwise significance level based on the chi-square approximation is inappropriate. Permutation is widely used to determine genome-wide significance. Theoretical approximations are available for simple experimental crosses. In this article, we propose a resampling procedure to assess the significance of genome-wide QTL mapping for experimental crosses. The proposed method is computationally much less intensive than the permutation procedure (in the order of 10(2) or higher) and is applicable to complex breeding designs and sophisticated genetic models that cannot be handled by the permutation and theoretical methods. The usefulness of the proposed method is demonstrated through simulation studies and an application to a Drosophila backcross.
Zou
Fei
F
Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina 27599-7420, USA. fzou@bios.unc.edu <fzou@bios.unc.edu>
Fine
Jason P
JP
Hu
Jianhua
J
Lin
D Y
DY
D000818:Animals; D002874:Chromosome Mapping / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004330:Drosophila / Q000235:genetics; D007178:Inbreeding; D040641:Quantitative Trait Loci; D012494:Sampling Studies