Methodology article

Generalizing Terwilliger's likelihood approach: a new score statistic to test for genetic association

Rachid el Galta¹ , Shirley Uitte de Willige² , Marieke CH de Visser² , Quinta Helmer¹ , Li Hsu³ and Jeanine J Houwing-Duistermaat¹

¹  Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands

²  Department of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, The Netherlands

³  Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA

author email corresponding author email

BMC Genetics 2007, 8:63doi:10.1186/1471-2156-8-63

Published:	24 September 2007

Abstract

Background:

In this paper, we propose a one degree of freedom test for association between a candidate gene and a binary trait. This method is a generalization of Terwilliger's likelihood ratio statistic and is especially powerful for the situation of one associated haplotype. As an alternative to the likelihood ratio statistic, we derive a score statistic, which has a tractable expression. For haplotype analysis, we assume that phase is known.

Results:

By means of a simulation study, we compare the performance of the score statistic to Pearson's chi-square statistic and the likelihood ratio statistic proposed by Terwilliger. We illustrate the method on three candidate genes studied in the Leiden Thrombophilia Study.

Conclusion:

We conclude that the statistic follows a chi square distribution under the null hypothesis and that the score statistic is more powerful than Terwilliger's likelihood ratio statistic when the associated haplotype has frequency between 0.1 and 0.4 and has a small impact on the studied disorder. With regard to Pearson's chi-square statistic, the score statistic has more power when the associated haplotype has frequency above 0.2 and the number of variants is above five.