A study of assessing genome-wise statistical significance for QTL mapping in the advanced backcross populations
Date Issued
2011
Date
2011
Author(s)
Guo, You-Tsz
Abstract
The statistical model of interval mapping for QTL (quantitative trait loci) detection is generally a normal mixture model. In detecting QTL, typically the presence of a QTL, i.e. the null hypothesis of no QTL, is tested over the all possible positions in the whole genome by using likelihood ratio test (LRT) statistics and the position with the maximum significant LRT statistic is regarded as the estimated QTL position. Under such a framework, the determination of the threshold values for declaring the significance of QTL detection has been recognized as a very important and challenging issue in QTL mapping. So far, most of the studies related to determining the threshold values are performed for the backcross and F$_2$ populations. In practical plant and animal breeding studies, advanced populations from backcross or F2 populations, which can have very different genome structures, are also very popular. In this study, we use score test statistics and Gaussian stochastic process to obtain the threshold values and investigate their behaviors for QTL mapping in the advanced backcross populations. To consider the specific genome structures of the advanced populations in the approach,
we derive the sets of transition equations to obtain the genotypic distributions of three and four genes and devise these genotypic frequencies into the formulations of the score test statistics and Gaussian processes to compute the approximate threshold values for different populations.
Simulation studies are performed to verify our approach.
Subjects
QTL
interval mapping
advanced backcross popultions
score test
Gaussian stochastic process
Type
thesis
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