A new association test to test multiple-marker association
Department of Mathematical Sciences
As a result of the availability of a very large numbers of single nucleotide polymorphisms, there has been increasing interest in genetic associations involving several closely linked loci. Methods for detection of association between traits and multiple genetic polymorphisms are being rapidly developed, which include the Hotelling's T2 test and the LD contrast (LDC) tests. The Hotelling's T2 test can be considered as a test to compare the means of the genotypic score in cases and controls; while the (LDC) tests can be considered as a test to compare the variance-covariance matrices of the genotypic score in cases and controls. In this article, we propose a likelihood ratio test which simultaneously compares the means and the variance-covariance matrices of the genotypic score in cases and controls. We use simulation studies to evaluate the type I error rate of the proposed test, and compare the power of the test with the Hotelling's T2 test and the LDC tests. The simulation results show that when marginal effects of the disease loci are strong, the proposed test is more powerful than the LDC tests and similar with or slightly less powerful than the Hotelling's T2 test. If there are interaction effects and weak or no marginal effects, the proposed method is more powerful than the Hotelling's T2 test and slightly more powerful than the LDC tests.
A new association test to test multiple-marker association.
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/3638