Permutation-based variance component test in generalized linear mixed model with application to multilocus genetic association study

Table 4 Results of the four genes in GAW17 data

Gene	Method	K	m	The significance levelα
Gene	Method	K	m	0.05	0.01	0.001
ELAVL4	Permutation	10	2	0.725	0.630	0.395
	Score			0.450	0.240	0.040
	Mixture (0.50)			0.640	0.485	0.335
	Mixture (0.65)			0.690	0.540	0.360
PTK2B	Permutation	18	3	0.600	0.470	0.290
	Score			0.085	0.030	0.000
	Mixture (0.50)			0.515	0.355	0.245
	Mixture (0.65)			0.540	0.405	0.255
PRKCB1	Permutation	20	1	0.550	0.355	0.255
	Score			0.095	0.030	0.005
	Mixture (0.50)			0.430	0.305	0.220
	Mixture (0.65)			0.465	0.315	0.225
SOS2	Permutation	9	2	0.545	0.400	0.235
	Score			0.160	0.030	0.005
	Mixture (0.50)			0.420	0.285	0.165
	Mixture (0.65)			0.450	0.325	0.185

Note: Permutation is the proposed permutation-based LRT, Score is the score-based sequence kernel association test given in Wu, et al. [31] that was originally developed in Lin (1997), Mixture (0.50) and Mixture (0.65) respectively correspond to the asymptotic 0.50:0.50 and 0.65:035 mixtures of chi-square distributions. In the last three columns of the table are the proportion of p-values less than α among the 200 replicates. Here K is the number of SNPs included in the gene, i.e., the number of the random effects contained in the logistic mixed effects model (5) and m is the number of causal SNPs.

ISSN: 1471-2288