. 2017 Aug 24;207(2):489–501. doi: 10.1534/genetics.117.300198

Table 4. Predictive ability in allele dosage models (mean ± SE).

Data sets	Traits	$G B L U P$	$E G B L U P$	$G_{H} B L U P$	$G_{H} B L U P \| G A$	$G_{H} B L U P \| G A$ ^*
Mouse	W6W	0.494 ± 0.001	*0.534 ± 0.002*	0.521 ± 0.001	0.496 ± 0.002	0.498 ± 0.001
	W7W	0.495 ± 0.002	*0.537 ± 0.002*	0.527 ± 0.002	0.502 ± 0.002	0.503 ± 0.002
	W8W	0.510 ± 0.001	0.523 ± 0.001	*0.531 ± 0.001*	0.518 ± 0.001	0.517 ± 0.001
	W10W	0.481 ± 0.001	0.491 ± 0.002	*0.507 ± 0.001*	0.487 ± 0.001	0.486 ± 0.001
	GSL	0.389 ± 0.001	*0.405 ± 0.002*	*0.405 ± 0.001*	0.388 ± 0.001	0.392 ± 0.001
	BMI	0.224 ± 0.002	0.206 ± 0.002	0.228 ± 0.002	*0.234 ± 0.002*	0.231 ± 0.002
	BL	0.264 ± 0.002	0.255 ± 0.002	0.268 ± 0.002	0.272 ± 0.002	*0.273 ± 0.002*
	%B220+	0.546 ± 0.002	0.541 ± 0.001	*0.549 ± 0.002*	0.543 ± 0.002	0.547 ± 0.002
	%CD3+	0.522 ± 0.002	0.495 ± 0.002	*0.531 ± 0.002*	0.517 ± 0.002	0.523 ± 0.002
	%CD4+	0.481 ± 0.002	0.454 ± 0.001	0.481 ± 0.001	0.473 ± 0.002	*0.482 ± 0.002*
	%CD8+	0.702 ± 0.001	0.668 ± 0.001	0.701 ± 0.001	0.706 ± 0.001	*0.707 ± 0.001*
	%CD4+/CD3+	0.638 ± 0.001	0.617 ± 0.001	0.633 ± 0.001	0.641 ± 0.001	*0.642 ± 0.001*
	%CD8+/CD3+	0.676 ± 0.001	0.636 ± 0.002	0.670 ± 0.002	*0.680 ± 0.001*	*0.680 ± 0.001*
	CD4+/CD8+	0.671 ± 0.001	0.636 ± 0.001	0.665 ± 0.001	0.674 ± 0.001	*0.675 ± 0.001*
	CD4Intensity	0.573 ± 0.002	0.550 ± 0.002	0.569 ± 0.002	0.570 ± 0.002	*0.574 ± 0.002*
	CD8Intensity	0.388 ± 0.002	*0.489 ± 0.002*	0.404 ± 0.002	0.379 ± 0.002	0.382 ± 0.002
DGRP	E2 (F)	0.202 ± 0.010	0.110 ± 0.012	0.210 ± 0.010	*0.225 ± 0.010*	0.208 ± 0.010
	E2 (M)	0.026 ± 0.010	0.038 ± 0.008	0.039 ± 0.010	*0.045 ± 0.009*	0.041 ± 0.011
	1-hexanol (F)	0.185 ± 0.010	0.209 ± 0.010	0.193 ± 0.009	*0.223 ± 0.009*	0.220 ± 0.010
	1-hexanol (M)	0.235 ± 0.009	0.225 ± 0.009	0.236 ± 0.009	*0.254 ± 0.008*	*0.254 ± 0.008*
Rice	DS_PH	0.486 ± 0.007	0.383 ± 0.006	0.499 ± 0.007	*0.522 ± 0.007*	*0.522 ± 0.007*
	DS_FLW	0.534 ± 0.005	0.405 ± 0.006	0.556 ± 0.005	*0.568 ± 0.005*	*0.568 ± 0.005*
	DS_YLD	0.289 ± 0.006	0.298 ± 0.008	0.285 ± 0.006	*0.323 ± 0.005*	*0.323 ± 0.005*
	WS_PH	0.482 ± 0.006	0.448 ± 0.007	0.496 ± 0.005	*0.516 ± 0.005*	*0.516 ± 0.005*
	WS_FLW	0.467 ± 0.007	0.412 ± 0.008	0.487 ± 0.006	*0.502 ± 0.006*	0.501 ± 0.006
	WS_YLD	0.258 ± 0.007	*0.299 ± 0.008*	0.242 ± 0.007	0.276 ± 0.008	0.276 ± 0.008
	Mean accuracy	0.431	0.418	0.440	0.444	0.444

For the DGRP data set, two traits for which the gene-annotation-based models show improved predictive ability are presented. W6W–W10W, body weight at 6–8 and 10 weeks; GSL, growth slope between 6 and 10 weeks of age; BMI, body mass index; BL, body length; %B220+, percentage of B220 cells; %CD3+, percentage of CD3 cells; %CD4+, percentage of CD4 cells; %CD8+, percentage of CD8 cells; %CD4+/CD3+, percentage of CD4 and CD3 cells; %CD8+/CD3+, percentage of CD8 and CD3 cells; CD4+/CD8+, ratio of CD4 to CD8 cells; CD4Intensity, CD4inCD3XGeoMean; CD8Intensity, CD8inCD3YGeoMean. F, female; M, male. DS, dry season; WS, wet season; PH, plant height; FLW, flower time; YLD, grain yield. For each trait (row), the values in boldface indicate the best prediction among all models and values in italic are those significantly higher than $G B L U P$ (P < 0.05, pairwise t-test).

Indicates models including gene-based haplotypes and unmapped SNPs simultaneously.