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 Citations (Scopus)

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
Publication statusPublished - 2009
Externally publishedYes

ASJC Scopus subject areas

  • Molecular Medicine
  • Genetics
  • Pharmacology

Fingerprint

Dive into the research topics of 'A new statistical screening approach for finding pharmacokinetics-related genes in genome-wide studies'. Together they form a unique fingerprint.

Cite this