TABLE 1.

Comparison of regression-based LD mapping methods with identity-by-descent (IBD) methods when the QTL explains 5% of the phenotypic variance

No. SNPs included in model	Marker density (no. SNPs in 11-cM region)
	6			10			20
		Geno	Haplo	IBD	Geno	Haplo	IBD	Geno	Haplo	IBD
Power to detect QTL (%)
1	67	—	48	77	—	52	85	—	53
2	69	69	69	78	79	78	85	84	81
4	68	59	76	79	70	82	84	74	77
6	—	—	75	—	—	85	—	—	83
8	—	—	—	—	—	84	—	—	—
Mean absolute error of position (cM) for significant QTL
1	1.05	—	1.14	0.79	—	0.90	0.64	—	0.81
2	1.20	1.21	1.17	0.92	0.92	0.87	0.67	0.64	0.64
4	1.38	1.34	1.11	1.31	1.30	0.85	0.88	0.91	0.62
6	—	—	1.21	—	—	0.86	—	—	0.62
8	—	—	—	—	—	0.93	—	—	—
Mean absolute error of position (cM) for all QTL
1	1.34	—	1.33	0.96	—	1.00	0.74	—	0.82
2	1.40	1.36	1.32	1.05	1.05	0.98	0.76	0.74	0.69
4	1.38	1.36	1.22	1.37	1.37	0.93	0.94	1.01	0.66
6	—	—	1.31	—	—	0.93	—	—	0.66
8	—	—	—	—	—	1.01	—	—	—

Power (detection at 1% regionwise level) and precision are shown for each LD mapping method: (1) Geno, regression on genotypes at 1, 2, or 4 adjacent SNPs; (2) Haplo, regression on assumed known haplotypes of 2 or 4 adjacent SNPs; and (3) IBD, identity-by-descent methods using single SNP genotype or assumed known haplotypes of 2, 4, 6, or 8 adjacent SNPs. In the base population, SNPs were simulated with allele frequency of 0.5 and in linkage equilibrium, and a QTL was simulated with unique alleles at the center of the 11-cM region. The other parameters are N_e = 100, number of generations since mutation = 100, and sample size in generation 100 = 500. Results are based on 10,000 replicates.