A Modified Maximum Contrast Method for Unequal Sample Sizes in Pharmacogenomic Studies

A Modified Maximum Contrast Method for Unequal Sample Sizes in Pharmacogenomic Studies 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 σ2, 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Statistical Applications in Genetics and Molecular Biology de Gruyter

A Modified Maximum Contrast Method for Unequal Sample Sizes in Pharmacogenomic Studies

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Publisher
de Gruyter
Copyright
Copyright © 2011 by the
ISSN
2194-6302
eISSN
1544-6115
DOI
10.2202/1544-6115.1560
pmid
23089824
Publisher site
See Article on Publisher Site

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 σ2, 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.

Journal

Statistical Applications in Genetics and Molecular Biologyde Gruyter

Published: Sep 7, 2011

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