A fast least-squares algorithm for population inference

BMC Bioinformatics

Table 5 Root mean squared error for P

K	N	α	AD	LS	FRAPPE	Significance	LSα
2	100	0.10	4.33	4.37	4.33	AD = FR = LS	4.36
2	100	0.50	5.13	5.17	5.14	AD = FR = LS	5.17
2	100	1.00	5.99	6.03	5.99	AD = FR = LS	6.03
2	100	2.00	7.24	7.28	7.29	AD = LS = FR	7.25
2	1000	0.10	1.37	1.42	1.38	AD < FR < LS	1.39
2	1000	0.50	1.62	1.65	1.63	AD = FR < LS	1.65
2	1000	1.00	1.90	1.93	1.92	AD < FR = LS	1.93
2	1000	2.00	2.52	2.58	2.82	AD = LS < FR	2.38
2	10000	0.10	0.46	0.57	0.46	AD < FR < LS	0.48
2	10000	0.50	0.52	0.56	0.53	AD < FR < LS	0.52
2	10000	1.00	0.60	0.61	0.62	AD < LS < FR	0.61
2	10000	2.00	0.81	0.87	1.14	AD < LS < FR	0.92
3	100	0.10	5.58	5.64	5.58	AD = FR = LS	5.62
3	100	0.50	7.37	7.42	7.38	AD = FR = LS	7.42
3	100	1.00	9.05	9.06	9.06	AD = FR = LS	9.06
3	100	2.00	11.36	11.33	11.39	LS = AD = FR	11.30
3	1000	0.10	1.78	1.87	1.78	AD = FR < LS	1.80
3	1000	0.50	2.35	2.40	2.35	AD = FR < LS	2.39
3	1000	1.00	2.97	3.00	3.01	AD < LS = FR	3.00
3	1000	2.00	4.11	4.14	4.41	AD = LS < FR	3.89
3	10000	0.10	0.61	0.82	0.62	AD < FR < LS	0.61
3	10000	0.50	0.78	0.84	0.78	AD = FR < LS	0.76
3	10000	1.00	0.93	0.95	0.98	AD < LS < FR	0.95
3	10000	2.00	1.35	1.36	1.82	AD = LS < FR	1.49
4	100	0.10	6.83	6.90	6.84	AD = FR = LS	6.87
4	100	0.50	9.61	9.63	9.62	AD = FR = LS	9.62
4	100	1.00	11.90	11.89	11.92	LS = AD = FR	11.89
4	100	2.00	14.94	14.89	15.01	LS = AD = FR	14.89
4	1000	0.10	2.16	2.28	2.16	AD = FR < LS	2.17
4	1000	0.50	3.10	3.15	3.11	AD = FR < LS	3.15
4	1000	1.00	4.04	4.06	4.08	AD < LS = FR	4.06
4	1000	2.00	5.61	5.62	5.88	AD = LS < FR	5.36
4	10000	0.10	0.76	1.02	0.77	AD = FR < LS	0.71
4	10000	0.50	1.04	1.11	1.04	AD = FR < LS	1.01
4	10000	1.00	1.28	1.30	1.33	AD < LS < FR	1.30
4	10000	2.00	1.87	1.87	2.36	AD = LS < FR	2.06

‘AD’ = Admixture with ε = MN×10^-4, ‘LS1’ = Least-squares with ε = MN×10^-4 and α = 1, ‘FR’ = FRAPPE with ε = 1. Bold values indicate significantly less error than those without bold. ‘<’ indicates significantly less at 4.6e-4 level, and ‘=’ indicates insignificant difference. ‘LSα’ = Least-squares with correct α provided only for reference.

ISSN: 1471-2105