Skip to main content

Table 7 Proportion of non-zero variant effects estimated per distribution, within each class of the BayesRC Lact model for Milk Yield

From: Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits

Model Class Number of Variants Proportion of Variant Effects per Distribution
N(0,0.0001\( \sigma \) 2 g) N(0,0.001\( \sigma \) 2 g) N(0,0.01\( \sigma \) 2 g)
AUS DANZ AUS DANZ AUS DANZ
BayesR SEQ N/A 909,143 0.86 % 0.58 % 0.01 % 0.01 % 0.002 % 0.001 %
BayesRC Lact Class I 3709 3.91 % 3.76 % 0.38 % 0.24 % 0.07 % 0.045 %
BayesRC Lact Class II 57,541 1.01 % 0.65 % 0.03 % 0.04 % 0.004 % 0.006 %
BayesRC Lact Class III 847,892 0.43 % 0.57 % 0.01 % 0.007 % 0.0003 % 0.0007 %
  1. Results are given for both AUS and DANZ training sets, and are compared to the distribution of variant effects in the BayesR SEQ model (bold figures)