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Table 5 Proportion of variance explained by markers (\(h_{M}^{2}\)) and polygenic effect (\(h_{A}^{2}\)) in the simulated dataset

From: Multi-breed genomic prediction using Bayes R with sequence data and dropping variants with a small effect

Data Analysis Drop \(h_{M}^{2}\) \(h_{A}^{2}\) \(h^{2}\)
HD FULL 0.0 0.57 0.02 0.59
S FULL 0.0 0.63 0.01 0.64
0.7 0.60 0.02 0.62
0.9 0.58 0.02 0.60
S KEPT 0.7 0.59 0.01 0.60
0.9 0.52 0.05 0.57
S + HD KEPT + HD 0.7 0.64 0.01 0.65
0.9 0.62 0.01 0.63
  1. \(h^{2} = h_{M}^{2} + h_{A}^{2}\), HD = HD genotypes used for prediction, S = sequence variants used for prediction, FULL = all variants analysed together, CHR = all variants analysed per chromosome, KEPT = variants selected by CHR reanalysed with all chromosomes together, KEPT + HD = variants selected by CHR and all HD variants reanalysed with all chromosomes together, dropProp = proportion of variants that is dropped after 10,000 MCMC iterations
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