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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)