A new statistical screening approach for finding pharmacokinetics-related genes in genome-wide studies

  • Y. Sato
  • , N. M. Laird
  • , A. Nagashima
  • , R. Kato
  • , T. Hamano
  • , A. Yafune
  • , N. Kaniwa
  • , Y. Saito
  • , E. Sugiyama
  • , S. R. Kim
  • , J. Furuse
  • , H. Ishii
  • , H. Ueno
  • , T. Okusaka
  • , N. Saijo
  • , J. I. Sawada
  • , T. Yoshida

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Biomedical researchers usually test the null hypothesis that there is no difference of the population mean of pharmacokinetics (PK) parameters between genotypes by the Kruskal-Wallis test. Although a monotone increasing pattern with a number of alleles is expected for PK-related genes, the Kruskal-Wallis test does not consider a monotonic response pattern. For detecting such patterns in clinical and toxicological trials, a maximum contrast method has been proposed. We show how that method can be used with pharmacogenomics data to a develop test of association. Further, using simulation studies, we compare the power of the modified maximum contrast method to those of the maximum contrast method and the Kruskal-Wallis test. On the basis of the results of those studies, we suggest rules of thumb for which statistics to use in a given situation. An application of all three methods to an actual genome-wide pharmacogenomics study illustrates the practical relevance of our discussion.

Original languageEnglish
Pages (from-to)137-146
Number of pages10
JournalPharmacogenomics Journal
Volume9
Issue number2
DOIs
StatePublished - 2009
Externally publishedYes

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