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Table 4 Description of datasets used for testing different parameters on the accuracy of imputation of GBS missing data

From: Low-depth genotyping-by-sequencing (GBS) in a bovine population: strategies to maximize the selection of high quality genotypes and the accuracy of imputation

Dataset ID Description Min. read depth MinMAFa Min. call rate Number of variants Variants shared with SNP50 Imputation program Estimated accuracy (%)
9 GBS 3 0.05 0.2 53,556 431 FImpute 71.1
10 GBS + SNP50 3 0.05 0.2 98,398 431 FImpute 84.8
11 GBS 3 0.05 0.3 40,208 334 FImpute 74.2
12 GBS + SNP50 3 0.05 0.3 88,573 334 FImpute 89.1
13 GBS 3 0.05 0.4 21,561 156 FImpute 77.5
14 GBS + SNP50 3 0.05 0.4 70,250 156 FImpute 91.9
15 GBS 4 0.02 0.2 55,727 395 FImpute 73.3
16 GBS + SNP50 4 0.02 0.2 100,297 395 FImpute 86.4
17 GBS 4 0.05 0.2 45,447 369 Beagle 70.9
  GBS 4 0.05 0.2 45,447 369 FImpute 71.2
18 GBS + SNP50 4 0.05 0.2 90.234 369 Beagle 78.5
  GBS + SNP50 4 0.05 0.2 90.234 369 FImpute 86.1
19 GBS 4 0.02 0.3 40,855 278 FImpute 75.9
20 GBS + SNP50 4 0.02 0.3 89,196 278 FImpute 90.3
21 GBS 4 0.05 0.3 31,662 254 Beagle 74.0
  GBS 4 0.05 0.3 31,662 254 FImpute 74.3
22 GBS + SNP50 4 0.05 0.3 80,190 254 Beagle 83.8
  GBS + SNP50 4 0.05 0.3 80,190 254 FImpute 89.3
23 GBS 4 0.02 0.4 22,331 98 FImpute 83.3
24 GBS + SNP50 4 0.02 0.4 70,983 98 FImpute 93.4
25 GBS 4 0.05 0.4 14,909 82 Beagle 81.2
  GBS 4 0.05 0.4 14,909 82 FImpute 80.8
26 GBS + SNP50 4 0.05 0.4 63,706 82 Beagle 89.8
  GBS + SNP50 4 0.05 0.4 63,706 82 FImpute 93.4
27 GBS 5 0.05 0.2 36,913 299 FImpute 70.0
28 GBS + SNP50 5 0.05 0.2 81,454 299 FImpute 85.4
29 GBS 5 0.05 0.3 22,685 166 FImpute 74.8
30 GBS + SNP50 5 0.05 0.3 71,360 166 FImpute 89.5
31 GBS 5 0.05 0.4 8818 42 FImpute 79.5
32 GBS + SNP50 5 0.05 0.4 57,719 42 FImpute 92.2
  1. aMinMAF: minimum minor allele frequency