Abstract
A statistical method for parametric density estimation based upon a mixture-of-genotypes model is developed for the thermostable phenol sulfotransferase (SULT1A1) activity which has a putative role in modifying risk for colon and prostate cancer/polyps. The EM algorithm for the general mixture model is modified to accommodate the genetic constraints and is used to estimate genotype frequencies from the distribution of the SULT1A1 phenotype. A parametric bootstrap likelihood ratio test is considered as a testing method for the number of mixing components. The size and power of the test is then investigated and compared with the conventional chi-squared test. The relative risk associated with genotypes defined by this model is also investigated through the generalized linear model. This analysis revealed that a genotype with the highest mean value of SULT1A1 activity has greater impact on cancer risk than others. This result suggests that the phenotype with a higher SULT1A1 activity might be important in studying the association between the cancer risk and SULT1A1 activity.
| Original language | English |
|---|---|
| Pages (from-to) | 707-719 |
| Number of pages | 13 |
| Journal | Biometrical Journal |
| Volume | 46 |
| Issue number | 6 |
| DOIs | |
| State | Published - Dec 2004 |
Keywords
- Bootstrap
- Density estimation
- EM algorithm
- Genotype
- Phenotype
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