Institute of Mathematics and Informatics Bulgarian Academy of Sciences
Abstract
2000 Mathematics Subject Classification: 62P10, 92D10, 92D30, 62F03In this article, we propose a novel candidate-gene association test that utilizes a set of tightly linked single nucleotide polymorphisms (SNPs). This is a powerful likelihood ratio test based on Gibbs random field model. We use simulation studies to evaluate the type I error rate of our proposed test, and compare its power with that of other candidate-gene association tests. The simulation results show that our proposed test has correct type I error rate, and is more powerful than the other tests in most cases considered in our simulation studies
