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


CONCLUSIONS
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.
el Galta
Rachid
R
Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands. rachid.elgalta@organon.com
Uitte de Willige
Shirley
S
de Visser
Marieke C H
MC
Helmer
Quinta
Q
Hsu
Li
L
Houwing-Duistermaat
Jeanine J
JJ
D016009:Chi-Square Distribution; D003198:Computer Simulation; D005340:Fibrinogen / Q000235:genetics; D006239:Haplotypes; D006801:Humans; D016013:Likelihood Functions; D015810:Linkage Disequilibrium; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci / Q000235:genetics*
D005340:Fibrinogen