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Genetics, Vol. 168, 2307-2316, December 2004, Copyright © 2004
doi:10.1534/genetics.104.031427
An Efficient Resampling Method for Assessing Genome-Wide Statistical Significance in Mapping Quantitative Trait Loci
Fei Zou*,1,
Jason P. Fine
,
Jianhua Hu* and
D. Y. Lin*
* Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina 27599-7420
Department of Statistics, University of Wisconsin, Madison, Wisconsin 53706
1 Corresponding author: Department of Biostatistics, University of North Carolina, 3107D McGavran-Greenberg Hall, CB 7420, Chapel Hill, NC 27599-7420.
E-mail: fzou{at}bios.unc.edu
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 102 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.
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