Using the realized relationship matrix to disentangle confounding factors for the estimation of genetic variance components of complex traits

Table 5 Estimated parameters for CC

	Model 1	Model 1-u^a	Model 1-f^b	Model 2	Model 3	Model 4
f ²	0.00	0.36	N/A	0.07	0.08	0.01
	(0.00)	(0.03)		(0.02)	(0.04)	(0.01)
c ²	0.01	0.02	0.01	0.00	0.00	0.00
	(0.01)	(0.02)	(0.01)	(0.01)	(0.01)	(0.00)
u ²	0.73	N/A	0.73	N/A	N/A	N/A
	(0.07)		(0.07)
g ²	N/A	N/A	N/A	0.71	0.05	0.01
				(0.03)	(0.03)	(0.01)
a ²	N/A	N/A	N/A	N/A	0.66	0.47
					(0.17)	(0.37)
δ ²	N/A	N/A	N/A	N/A	N/A	0.49
						(0.37)
Log L	-2373.14	-2381.68	-2373.14	-2190.39	-1954.99^c	-974.46^d
					(7.88)	(29.48)
Parameters	f, c, u	f, c	c, u	f, c, g	f, c, g, α	f, c, g, α, δ
AIC^e	4752.28	4767.36	4750.26	4387.84	3931.74	2013.88

Proportion of total phenotypic variance due to family (f), cage (c), and polygenic effects based on pedigree (u), realized relationships (g), and specific additive and dominance SNP effects (α and δ ) when using model 1, 2, 3 and 4 for CC
^cThe averaged log-likelihood during MCMC process (the averaged number of parameters due to additive SNP in the model)
^dThe average log-likelihood during MCMC process (the averaged number of parameters due to additive and dominance SNP in the model)

ISSN: 1297-9686