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Counting interval mapping of quantitative trait

Author: ZhaoLiZuo
Tutor: MaWeiJun
School: Heilongjiang University
Course: Applied Mathematics
Keywords: Quantitative traits EM algorithm District simple positioning Likelihood Ratio Test Multivariate Poisson distribution
CLC: O212.7
Type: Master's thesis
Year: 2011
Downloads: 3
Quote: 0
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Abstract


In the human, animal and plant towel , change of many quantitative traits and genetic effects on quantitative trait locus (QTL) position , electricity is enough to save the entire genome to find the effect of leather trait loci position , with a certain scientific and economic value in recent years , the district asked positioning method is widely applied to the QTL genetic mapping towel , biology towel facing one of the most cover = challenges to foot based on biological traits on , not environmental factors adaptability to understand the genetic mechanisms , and how to use this knowledge to predict environmental change , biological structure , organization , and functions a series of anti should an organism be planted in different environments , will produce a series of performance -type organisms such environmental changes J. : Students the ability to change its performance scraping it enough species diversity in this article by genetics gene-environment interactions , we use the interval mapping method , consider counting the number of grass traits called phenotypic plasticity QTL parameter Estimation of the QTL in different environments by phenotypic plasticity control fitting trait phenotype foot counts , so in order to meet the needs of the traits , we applied multivariate Poisson distribution and use of the EM algorithm QTL location and Poisson parameters to obtain maximum likelihood estimation (MLE) synchronization estimate , so the potential to improve the effectiveness of our model estimated elm experience some assumptions , these assumptions are used to explain phenotypic plasticity , ie QTL with manifestations of some minor , simulation study shows the superiority of the algorithm for the QTL position and Poisson parameter estimation in different environments , and the contrast with the conventional method while a simulation result of the hypothesis test also showed a our method has the correct first ' the class anchor error rate and higher efficacy

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CLC: > Mathematical sciences and chemical > Mathematics > Probability Theory and Mathematical Statistics > Mathematical Statistics > Non-parametric statistics
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