Locally epistatic models for genome-wide prediction and association by importance sampling

Table 1 Summary of the features of the datasets and the hyper-parameter settings for the results presented in Fig. 5

Dataset	Number of individuals	Number of SNPs	Traits	Mean depth	Nrules	Nsplits	Proprow	Propcol
Rice	299	73K	PH, FLW, LG, GRL, GRW, 1000GW, YLD	4	500	5	.3	.1
Mouse	1940	12K	Body weight, growth slope		2000	10	.1	.05
Maize	4676	125K	GDD_DTS	2	1000	10	.1	.05
			GDD_DTA, GDD_ASI, DTS	2	200	40 (using hotspots)	.1	.05
			DTA, ASI, PH, EH
			PH.EH, EHdivPH, PHdivDTR
Wheat	337	3355	FD, PMD, PH, YLD, WGP	1	500	2	.3	.1
			HD, WAX

Trait Names: GDD_DTA growing degree days to silk, GDD_DTA growing degree days to anthesis, GDD_ASI growing degree days to anthesis-silking interval, DTS days to silking, DTA days to anthesis, ASI anthesis silking interval days, PH plant height, EH ear height, PH-EH PH minus EH, EHdivPH EH divided by PH, PHdivDTR PH divided by days to anthesis FLW flag leaf width, LG lodging, GRL grain length, GRW grain weight, 1000GW thousand grain weight, YLD yield, FD flowering day, PMD physiological maturity day, WGP whole grain protein, HD heading date Julian, WAX waxiness

ISSN: 1297-9686