Assessing accuracy of imputation using different SNP panel densities in a multi-breed sheep population

Table 4 Accuracy of genotype imputation and computing time for BEAGLE and FIMPUTE algorithms

Scenario	CR_F^a	r²_F^b	Run Time_F m:s	CR_B^c	r²_B^d	Run Time_ B h:m:s	Mean Top10^e	Min Top10^e	Max Top10^e
1_5K50K	86.98	78.75	00:57	83.80	73.80	02:16:25	0.115	0.034	0.234
1B_5KHD_1STEP	87.61	80.73	06:51	84.10	74.00	23:12:35	0.115	0.034	0.234
1B_5KHD_2STEP	93.28	89.6	–	NA	NA	NA	0.115	0.034	0.234
2_50KHD	97.56	96.2	07:42	96.98	95.42	21:55:35	0.115	0.034	0.234
3_5K50K	84.35	74.15	00:53	82.12	70.94	03:15:10	0.090	0.033	0.179
3B_5KHD	85.3	76.85	06:43	82.23	71.12	27:17:35	0.090	0.033	0.179
4_50KHD	97.25	95.71	07:11	96.63	94.91	12:33:02	0.090	0.033	0.179
5_5K50K	87.19	78.98	01:08	83.58	73.37	03:18:52	0.097	0.037	0.252
5B_5KHD	87.68	80.81	08:45	83.99	76.00	25:16:22	0.097	0.037	0.252
6_50KHD	98.06	97.01	09:14	Failed	Failed	Failed	0.097	0.037	0.252

^aCR_F = concordance rate using the FIMPUTE software
^br²_F = Squared Pearson correlation using the FIMPUTE software
^cCR_B = concordance rate using the BEAGLE software
^dr²_B = Squared Pearson correlation using the BEAGLE software
^eMean Top10, Min Top10 and Max Top10 = mean, min and max relationship among the 10 most related animals between the reference and imputed sets

ISSN: 1297-9686