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A mixture-of-genotypes model for the distribution of thermostable phenol sulfotransferase activity

  • Jungnam Joo
  • , Hongshik Ahn
  • , Robert R. Delongchamp
  • , Susan A. Nowell
  • , Nicholas P. Lang

Research output: Contribution to journalArticlepeer-review

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 languageEnglish
Pages (from-to)707-719
Number of pages13
JournalBiometrical Journal
Volume46
Issue number6
DOIs
StatePublished - Dec 2004

Keywords

  • Bootstrap
  • Density estimation
  • EM algorithm
  • Genotype
  • Phenotype

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