Score Test Statistics for QTL Mapping under Selective Genotyping

• Main Authors: Yu-Chuang Fang, 房佑嬙
• Other Authors: Chen-Hung Kao
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/14476325888871324775

碩士 === 國立臺灣大學 === 農藝學研究所 === 101 === The detection of quantitative trait loci (QTL) that govern many biologically and economically important traits is an important task in plant and animal breeding. Using genetic marker data, QTL mapping technique has been known to be an efficient tool to detect QTL location and estimate the QTL effect. In QTL mapping, selective genotyping, which genotypes only the individuals from high and low phenotypic values, is one of the most common strategies that can reduce the cost of marker genotyping and at the same time increase efficiency in QTL detection. In this thesis, with the posterior model of selective genotyping proposed by Lee et al. (2013), we derived score test statistic for the model and applied it to QTL detection. Moreover, we compare this score test statistics with that of the currently used model, and the threshold values of the score test statistics under selective genotyping are also investigated. As the result, we found out that the two score test statistics for the posterior model and currently used model perform equally well under single-QTL model. In the future, we intend to extend the single-QTL posterior model to multiple-QTL model for QTL detection under selective genotyping.