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Table 7 Summary statistics of imputation accuracy, using BEAGLE and FImpute

From: Accuracy of genotype imputation in Nelore cattle

   

BEAGLE (FImpute)

Anal.1

Validation set

SNP chip2

Minimum

Maximum

Mean

SD

24 (1)

Young sire

7 K

0.7525 (0.8003)

0.9717 (0.9845)

0.8982 (0.9257)

0.0392 (0.0346)

25 (3)

Young sire

GGP20Ki

0.8603 (0.8988)

0.9951 (0.9963)

0.9614 (0.9771)

0.0225 (0.0143)

26 (4)

Young sire

GGP75Ki

0.9142 (0.9568)

0.9986 (0.9990)

0.9842 (0.9922)

0.0120 (0.0056)

27 (8)

Young sire

15K_eml

0.8788 (0.9211)

0.9976 (0.9981)

0.9714 (0.9840)

0.0183 (0.0107)

28 (9)

Young sire

11a7 K

0.8773 (0.9163)

0.9979 (0.9975)

0.9697 (0.9823)

0.0190 (0.0117)

29 (12)

Young sire

48a7 K

0.9214 (0.9628)

0.9989 (0.9992)

0.9860 (0.9931)

0.0111 (0.0049)

30 (17)

Dam

7 K

0.6969 (0.7096)

0.9576 (0.9656)

0.8501 (0.8791)

0.0441 (0.0474)

31 (19)

Dam

GGP20Ki

0.8124 (0.8357)

0.9874 (0.9923)

0.9321 (0.9566)

0.0288 (0.0211)

32 (20)

Dam

GGP75Ki

0.8645 (0.9291)

0.9946 (0.9976)

0.9692 (0.9846)

0.0198 (0.0082)

33 (21)

Dam

15K_eml

0.8296 (0.8711)

0.9904 (0.9954)

0.9456 (0.9680)

0.0254 (0.0164)

34 (22)

Dam

11a7K

0.8249 (0.8640)

0.9893 (0.9951)

0.9430 (0.9658)

0.0260 (0.0173)

35 (23)

Dam

48a7K

0.8677 (0.9363)

0.9954 (0.9980)

0.9715 (0.9864)

0.0193 (0.0073)

  1. 1Results of imputation analyses using BEAGLE or FImpute (between brackets) and different validation sets (young sires and dams); the numbers of each analysis refer to those from Figure 1; 2as described in the section ¿SNP chips¿ of ¿Methods¿; SD = standard deviation.