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Table 3 Posterior mean proportion of variance explained by markers (h 2) using different Bayesian methods, and number of chromosome segments and SNPs involved in the very low-density panel selection by K-means and random cross-validation group

From: Tag SNP selection for prediction of tick resistance in Brazilian Braford and Hereford cattle breeds using Bayesian methods

Group

h 2

SNP panel selection

BayesB π = 0.99

BayesB π = 0.999

BayesA full

BayesA tag

Top windowsa

Top SNPsb

Tag SNPsc

K-means 1

0.13

0.06

0.19

0.10

41

741

47

K-means 2

0.10

0.04

0.17

0.09

46

878

57

K-means 3

0.12

0.05

0.18

0.12

39

727

67

K-means 4

0.12

0.05

0.18

0.11

48

941

79

K-means 5

0.11

0.04

0.18

0.10

43

799

55

Random 1

0.12

0.05

0.18

0.11

42

778

57

Random 2

0.11

0.04

0.18

0.12

53

956

70

Random 3

0.11

0.05

0.18

0.13

52

1008

86

Random 4

0.12

0.05

0.18

0.11

48

900

78

Random 5

0.11

0.04

0.18

0.12

55

1005

79

  1. aTop windows represents the number of windows that explained above 0.2% of the genetic variance in the BayesB (π = 0.99) GWAS analysis
  2. bTop SNPs represents the number of SNPs included in those top windows
  3. cTag SNPs represents the number of SNPs selected as more informative according to the criteria based on model frequency and t.like statistics, linkage disequilibrium and minor allele frequency
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Genetics Selection Evolution

ISSN: 1297-9686