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

Yasunori 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 journalArticle

10 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 Apr 1
Externally publishedYes

Fingerprint

Pharmacokinetics
Genome
Genes
Pharmacogenetics
Toxicology
Alleles
Genotype
Research Personnel
Clinical Trials
Population

ASJC Scopus subject areas

  • Molecular Medicine
  • Genetics
  • Pharmacology

Cite this

A new statistical screening approach for finding pharmacokinetics-related genes in genome-wide studies. / Sato, Yasunori; Laird, N. M.; Nagashima, A.; Kato, R.; Hamano, T.; Yafune, A.; Kaniwa, N.; Saito, Y.; Sugiyama, E.; Kim, S. R.; Furuse, J.; Ishii, H.; Ueno, H.; Okusaka, T.; Saijo, N.; Sawada, J. I.; Yoshida, T.

In: Pharmacogenomics Journal, Vol. 9, No. 2, 01.04.2009, p. 137-146.

Research output: Contribution to journalArticle

Sato, Y, Laird, NM, Nagashima, A, Kato, R, Hamano, T, Yafune, A, Kaniwa, N, Saito, Y, Sugiyama, E, Kim, SR, Furuse, J, Ishii, H, Ueno, H, Okusaka, T, Saijo, N, Sawada, JI & Yoshida, T 2009, 'A new statistical screening approach for finding pharmacokinetics-related genes in genome-wide studies', Pharmacogenomics Journal, vol. 9, no. 2, pp. 137-146. https://doi.org/10.1038/tpj.2008.17
Sato, Yasunori ; Laird, N. M. ; Nagashima, A. ; Kato, R. ; Hamano, T. ; Yafune, A. ; Kaniwa, N. ; Saito, Y. ; Sugiyama, E. ; Kim, S. R. ; Furuse, J. ; Ishii, H. ; Ueno, H. ; Okusaka, T. ; Saijo, N. ; Sawada, J. I. ; Yoshida, T. / A new statistical screening approach for finding pharmacokinetics-related genes in genome-wide studies. In: Pharmacogenomics Journal. 2009 ; Vol. 9, No. 2. pp. 137-146.
@article{8a1b5d79c7dc4a82a6b62b8d17300bdc,
title = "A new statistical screening approach for finding pharmacokinetics-related genes in genome-wide studies",
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.",
author = "Yasunori Sato and Laird, {N. M.} and A. Nagashima and R. Kato and T. Hamano and A. Yafune and N. Kaniwa and Y. Saito and E. Sugiyama and Kim, {S. R.} and J. Furuse and H. Ishii and H. Ueno and T. Okusaka and N. Saijo and Sawada, {J. I.} and T. Yoshida",
year = "2009",
month = "4",
day = "1",
doi = "10.1038/tpj.2008.17",
language = "English",
volume = "9",
pages = "137--146",
journal = "Pharmacogenomics Journal",
issn = "1470-269X",
publisher = "Nature Publishing Group",
number = "2",

}

TY - JOUR

T1 - A new statistical screening approach for finding pharmacokinetics-related genes in genome-wide studies

AU - Sato, Yasunori

AU - Laird, N. M.

AU - Nagashima, A.

AU - Kato, R.

AU - Hamano, T.

AU - Yafune, A.

AU - Kaniwa, N.

AU - Saito, Y.

AU - Sugiyama, E.

AU - Kim, S. R.

AU - Furuse, J.

AU - Ishii, H.

AU - Ueno, H.

AU - Okusaka, T.

AU - Saijo, N.

AU - Sawada, J. I.

AU - Yoshida, T.

PY - 2009/4/1

Y1 - 2009/4/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=63149101537&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=63149101537&partnerID=8YFLogxK

U2 - 10.1038/tpj.2008.17

DO - 10.1038/tpj.2008.17

M3 - Article

C2 - 19104505

AN - SCOPUS:63149101537

VL - 9

SP - 137

EP - 146

JO - Pharmacogenomics Journal

JF - Pharmacogenomics Journal

SN - 1470-269X

IS - 2

ER -