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QTL Gene Imprinting Effect On SNP Estimation And Testing

Posted on:2015-03-25Degree:MasterType:Thesis
Country:ChinaCandidate:J RenFull Text:PDF
GTID:2260330431457449Subject:Applied Mathematics
Abstract/Summary:PDF Full Text Request
This paper studies the problem of estimating and testing the QTL’s imprintingefect based on single nucleotide polymorphism(SNP).Genomic imprinting(also known as genetic imprinting)represents the diferencesfrom paternal and maternal chromosomes or alleles in the functional, thus ofspringby diferent parents would cause diferent phenotypes when the same chromosome orgenetic changed, is an inheritance of non-Mendelian. Currently, genomic imprintinghas been considered playing an important role in the form of complex human diseasesand pathogenesis. Imprinting mechanism has become the researching focus of manygenetic diseases, however we haven’t known some aspects such as the number ofimprinted genes、their chromosomal location as well as the interactions with othergenes or environments, which limits our accuracy of concluding about the structureand pathogenesis of human complex disease genes.Comparing to the variation of DNA genetic, Heritable information is more sus-ceptible by environment within the context of epigenetic, and is more prone to occurdynamic and reversible changes. Briefy, diferent environment factors have diferentefects to the phenotype of the organism advanced representative type. Accordingly,studying IQTL’s imprinting efect in this article, we take account of that its impactnot only by a simple additive, dominance and imprinting efect, may also be afect-ed by environment efect、the interaction efects of genes and environments, so weestablish the mixed linear model with environment efects in order to achieve thepurpose of explaining statistical signifcance of the human complex diseases causedby genomic imprinting more efectively. this article will apply the Bayesian statisti-cal methods to estimate and test of QTL’s imprint efect.
Keywords/Search Tags:Genetic imprinting, Environment efect, QTL×environment efect, Mixed linear model, MCMC method
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