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Table 7 Average number of variants per distribution over the number of iterations in the real dataset

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

Trait Data Analysis DropProp Number of variants per distribution
0 \(\sigma_{g}^{2}\) 0.0001 \(\sigma_{g}^{2}\) 0.001 \(\sigma_{g}^{2}\) 0.01 \(\sigma_{g}^{2}\)
Milk HD FULL 0 627,503 4299 22 10
S KEPT 0.9 483,521 6603 17 6
S + HD KEPT + HD 0.9 1076,643 8927 22 6
Fat HD FULL 0 627,510 4312 9 4
S KEPT 0.9 483,614 6307 7 4
S + HD KEPT + HD 0.9 1080,078 8890 9 3
Prot HD FULL 0 627,347 4476 9 3
S KEPT 0.9 482,957 6352 8 3
S + HD KEPT + HD 0.9 1078,647 9025 9 2
Fert HD FULL 0 625,899 5668 260 8
S KEPT 0.9 548,382 5715 310 5
S + HD KEPT + HD 0.9 1135,712 10,569 436 7
  1. Prot = protein, fert = fertility, HD = HD genotypes used for prediction, S = sequence variants used for prediction, FULL = all variants analysed together, KEPT = variants selected per chromosome reanalysed with all chromosomes together, KEPT + HD = variants selected per chromosome and all HD variants reanalysed with all chromosomes together, dropProp = proportion of variants dropped after 10,000 MCMC iterations, \(\sigma_{g}^{2}\) = additive genetic variance
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