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

Table 7 Accuracy (acc) and regression (reg) in the prediction of phenotypes

Trait	Model 1		Model 2		Model 3		Model 4
	acc	reg	acc	reg	acc	reg	acc	reg
	prediction within full-sib families
FDC	0.21	1.03	0.26	0.94	0.28	0.87	0.35	0.87
	(0.04)	(0.4)	(0.04)	(0.16)	(0.05)	(0.19)	(0.03)	(0.08)
REP	0.44	1.01	0.51	0.99	0.52	0.95	0.52	0.93
	(0.02)	(0.10)	(0.02)	(0.07)	(0.02)	(0.06)	(0.02)	(0.07)
WT	0.54	1	0.57	0.97	0.57	0.95	0.56	0.93
	(0.03)	(0.13)	(0.03)	(0.06)	(0.03)	(0.09)	(0.04)	(0.1)
CC	0.54	0.97	0.65	0.97	0.69	0.93	0.87	0.99
	(0.02)	(0.06)	(0.01)	(0.05)	(0.01)	(0.05)	(0.03)	(0.02)
prediction across full-sib families
FDC	-0.02	-0.53	0.16	0.89	0.19	0.84	0.29	0.85
	(0.04)	(1.94)	(0.04)	(0.23)	(0.07)	(0.27)	(0.05)	(0.08)
REP	0.12	0.83	0.31	0.81	0.36	0.8	0.35	0.75
	(0.05)	(0.4)	(0.04)	(0.15)	(0.05)	(0.14)	(0.04)	(0.13)
WT	0.18	0.97	0.3	0.97	0.3	0.87	0.28	0.76
	(0.04)	(0.28)	(0.03)	(0.13)	(0.04)	(0.2)	(0.06)	(0.23)
CC	0.17	0.85	0.46	0.9	0.53	0.8	0.78	0.95
	(0.04)	(0.2)	(0.07)	(0.17)	(0.09)	(0.17)	(0.09)	(0.13)

The average of correlations of actual and predicted phenotypes (standard deviations), and regression of the true phenotypes on predicted phenotypes (standard deviations) over 10 replicates when using model 1, 2, 3 and 4 for the traits

ISSN: 1297-9686