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Table 3 Overview of scenarios

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

Scenario Data Strategy DropIter DropProp Simulation Real
HD_FULL_D0 HD FULL 0 Y Y
S_FULL_D0 SEQ FULL 0 Y N
S_FULL_D0.25 SEQ FULL 0, 200 or 10,000 0.25 Y N
S_FULL_D0.50 SEQ FULL 0, 200 or 10,000 0.50 Y N
S_FULL_D0.7 SEQ FULL 0, 200 or 10,000 0.70 Y N
S_FULL_D0.9 SEQ FULL 0, 200 or 10,000 0.90 Y N
S_CHR_D0 SEQ CHR 0 0 Y N
S_CHR_D0.7 SEQ CHR 10,000 0.70 Y N
S_CHR_D0.9 SEQ CHR 10,000 0.90 Y N
S_KEPT_D0.7 SEQ KEPT 10,000 0.70 Y N
S_KEPT_D0.9 SEQ KEPT 10,000 0.90 Y Y
S + HD_KEPT + HD_D0.7 SEQ + HD KEPT + HD 10,000 0.70 Y N
S + HD_KEPT + HD_D0.9 SEQ + HD KEPT + HD 10,000 0.90 Y N
  1. 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 dropIter MCMC iterations, simulation and real indicate whether the scenario was analysed in the simulated and real datasets
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