Bayesian Variable Selection in Logistic Mixed Models for WTCCC Data Sets
碩士 === 國立彰化師範大學 === 統計資訊研究所 === 100 === In recent years, single nucleotide polymorphism (SNP) is widely used in biological and medical fields. Many scientists and statisticians try to find significant SNPs associated with disease from genome-wide data. In this thesis, we not only detect association...
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| Format: | Others |
| Language: | zh-TW |
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2012
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| Online Access: | http://ndltd.ncl.edu.tw/handle/06219710380797564945 |
| Summary: | 碩士 === 國立彰化師範大學 === 統計資訊研究所 === 100 === In recent years, single nucleotide polymorphism (SNP) is widely used in biological and medical fields. Many scientists and statisticians try to find significant SNPs associated with disease from genome-wide data. In this thesis, we not only detect association between SNPs and disease under logistic mixed models, but also examine heterogeneity among geographical regions by adding random effects. We use stochastic search variable selection (SSVS) to select fixed and random effects simultaneously. Furthermore, we illustrate the SSVS with seven complex human diseases in the WTCCC (Wellcome Trust Case Control Consortium) data.
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