An efficient resampling method for assessing genome-wide statistical significance in mapping quantitative trait loci

51Citations
Citations of this article
54Readers
Mendeley users who have this article in their library.

Abstract

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.

Cite

CITATION STYLE

APA

Zou, F., Fine, J. P., Hu, J., & Lin, D. Y. (2004). An efficient resampling method for assessing genome-wide statistical significance in mapping quantitative trait loci. Genetics, 168(4), 2307–2316. https://doi.org/10.1534/genetics.104.031427

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free