A modified maximum contrast method for unequal sample sizes in pharmacogenomic studies

Kengo Nagashima, Yasunori Sato, Chikuma Hamada

Research output: Contribution to journalArticle

Abstract

In pharmacogenomic studies, biomedical researchers commonly analyze the association between genotype and biological response by using the Kruskal-Wallis test or one-way analysis of variance (ANOVA) after logarithmic transformation of the obtained data. However, because these methods detect unexpected biological response patterns, the power for detecting the expected pattern is reduced. Previously, we proposed a combination of the maximum contrast method and the permuted modified maximum contrast method for unequal sample size in pharmacogenomic studies. However, we noted that the distribution of the permuted modified maximum contrast statistic depends on nuisance parameter ?2, which is the population variance. In this paper, we propose a modified maximum contrast method with a statistic that does not depend on the nuisance parameter. Furthermore, we compare the performance of these methods via simulation studies. The simulation results showed that the modified maximum contrast method gave the lowest false-positive rate; therefore, this method is powerful for detecting the true response patterns in some conditions. Further, it is faster and more accurate than the permuted modified maximum contrast method. On the basis of these results, we suggest a rule of thumb to select the appropriate method in a given situation.

Original languageEnglish
Article number41
JournalStatistical Applications in Genetics and Molecular Biology
Volume10
Issue number1
DOIs
Publication statusPublished - 2011 Oct 11
Externally publishedYes

Fingerprint

Unequal
Sample Size
Statistics
Analysis of variance (ANOVA)
Nuisance Parameter
Statistic
Pharmacogenomic Testing
Pharmacogenetics
Analysis of variance
Genotype
False Positive
Lowest
Analysis of Variance
Logarithmic
Research Personnel
Simulation Study
Population

Keywords

  • biological response pattern
  • maximum contrast statistic
  • multiple contrast statistics
  • pharmacokinetics-related gene
  • unequal sample size

ASJC Scopus subject areas

  • Statistics and Probability
  • Molecular Biology
  • Genetics
  • Computational Mathematics

Cite this

A modified maximum contrast method for unequal sample sizes in pharmacogenomic studies. / Nagashima, Kengo; Sato, Yasunori; Hamada, Chikuma.

In: Statistical Applications in Genetics and Molecular Biology, Vol. 10, No. 1, 41, 11.10.2011.

Research output: Contribution to journalArticle

@article{99b570936c374560ad4e01c2ff7c88c9,
title = "A modified maximum contrast method for unequal sample sizes in pharmacogenomic studies",
abstract = "In pharmacogenomic studies, biomedical researchers commonly analyze the association between genotype and biological response by using the Kruskal-Wallis test or one-way analysis of variance (ANOVA) after logarithmic transformation of the obtained data. However, because these methods detect unexpected biological response patterns, the power for detecting the expected pattern is reduced. Previously, we proposed a combination of the maximum contrast method and the permuted modified maximum contrast method for unequal sample size in pharmacogenomic studies. However, we noted that the distribution of the permuted modified maximum contrast statistic depends on nuisance parameter ?2, which is the population variance. In this paper, we propose a modified maximum contrast method with a statistic that does not depend on the nuisance parameter. Furthermore, we compare the performance of these methods via simulation studies. The simulation results showed that the modified maximum contrast method gave the lowest false-positive rate; therefore, this method is powerful for detecting the true response patterns in some conditions. Further, it is faster and more accurate than the permuted modified maximum contrast method. On the basis of these results, we suggest a rule of thumb to select the appropriate method in a given situation.",
keywords = "biological response pattern, maximum contrast statistic, multiple contrast statistics, pharmacokinetics-related gene, unequal sample size",
author = "Kengo Nagashima and Yasunori Sato and Chikuma Hamada",
year = "2011",
month = "10",
day = "11",
doi = "10.2202/1544-6115.1560",
language = "English",
volume = "10",
journal = "Statistical Applications in Genetics and Molecular Biology",
issn = "1544-6115",
publisher = "Berkeley Electronic Press",
number = "1",

}

TY - JOUR

T1 - A modified maximum contrast method for unequal sample sizes in pharmacogenomic studies

AU - Nagashima, Kengo

AU - Sato, Yasunori

AU - Hamada, Chikuma

PY - 2011/10/11

Y1 - 2011/10/11

N2 - In pharmacogenomic studies, biomedical researchers commonly analyze the association between genotype and biological response by using the Kruskal-Wallis test or one-way analysis of variance (ANOVA) after logarithmic transformation of the obtained data. However, because these methods detect unexpected biological response patterns, the power for detecting the expected pattern is reduced. Previously, we proposed a combination of the maximum contrast method and the permuted modified maximum contrast method for unequal sample size in pharmacogenomic studies. However, we noted that the distribution of the permuted modified maximum contrast statistic depends on nuisance parameter ?2, which is the population variance. In this paper, we propose a modified maximum contrast method with a statistic that does not depend on the nuisance parameter. Furthermore, we compare the performance of these methods via simulation studies. The simulation results showed that the modified maximum contrast method gave the lowest false-positive rate; therefore, this method is powerful for detecting the true response patterns in some conditions. Further, it is faster and more accurate than the permuted modified maximum contrast method. On the basis of these results, we suggest a rule of thumb to select the appropriate method in a given situation.

AB - In pharmacogenomic studies, biomedical researchers commonly analyze the association between genotype and biological response by using the Kruskal-Wallis test or one-way analysis of variance (ANOVA) after logarithmic transformation of the obtained data. However, because these methods detect unexpected biological response patterns, the power for detecting the expected pattern is reduced. Previously, we proposed a combination of the maximum contrast method and the permuted modified maximum contrast method for unequal sample size in pharmacogenomic studies. However, we noted that the distribution of the permuted modified maximum contrast statistic depends on nuisance parameter ?2, which is the population variance. In this paper, we propose a modified maximum contrast method with a statistic that does not depend on the nuisance parameter. Furthermore, we compare the performance of these methods via simulation studies. The simulation results showed that the modified maximum contrast method gave the lowest false-positive rate; therefore, this method is powerful for detecting the true response patterns in some conditions. Further, it is faster and more accurate than the permuted modified maximum contrast method. On the basis of these results, we suggest a rule of thumb to select the appropriate method in a given situation.

KW - biological response pattern

KW - maximum contrast statistic

KW - multiple contrast statistics

KW - pharmacokinetics-related gene

KW - unequal sample size

UR - http://www.scopus.com/inward/record.url?scp=80053505502&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80053505502&partnerID=8YFLogxK

U2 - 10.2202/1544-6115.1560

DO - 10.2202/1544-6115.1560

M3 - Article

C2 - 23089824

AN - SCOPUS:80053505502

VL - 10

JO - Statistical Applications in Genetics and Molecular Biology

JF - Statistical Applications in Genetics and Molecular Biology

SN - 1544-6115

IS - 1

M1 - 41

ER -