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. 2014 Oct 10;46(1):69. doi: 10.1186/s12711-014-0069-1

Table 4.

Average (standard deviation) imputation accuracy, for different imputation analyses using FImpute

Analysis 1 SNP chip 2 Nb (%) SNPs to be imputed CORR 3 PERC 4
1 7 K 435509 (99.1) 0.9257 (0.0346) 90.56 (4.09)
2 50 K 418581 (95.2) 0.9783 (0.0136) 97.14 (1.76)
3 GGP20Ki 426145 (96.9) 0.9771 (0.0143) 96.96 (1.87)
4 GGP75Ki 383426 (87.2) 0.9922 (0.0056) 98.93 (0.76)
5 15K_e 424451 (96.6) 0.9784 (0.0135) 97.15 (1.75)
6 15K_em 424422 (96.5) 0.9820 (0.0120) 97.58 (1.61)
7 15K_el 424422 (96.5) 0.9763 (0.0138) 96.87 (1.77)
8 15K_eml 424422 (96.5) 0.9840 (0.0107) 97.85 (1.43)
9 11a7 K 424305 (96.5) 0.9823 (0.0117) 97.63 (1.54)
10 17a7 K 418025 (95.1) 0.9864 (0.0093) 98.17 (1.24)
11 27a7 K 408204 (92.9) 0.9897 (0.0072) 98.60 (0.97)
12 48a7 K 387005 (88.0) 0.9931 (0.0049) 99.05 (0.67)

1Imputation analyses using FImpute (considering family information) and 202 young sires as the validation set; the numbers of each analysis refer to those in brackets from Figure 1; 2as described in the section “SNP chips” of “Methods”; 3CORR: Pearson’s correlation between imputed and observed genotypes; 4PERC: percentage of correctly imputed genotypes.