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Table 3 Estimated parameters for REP

From: Using the realized relationship matrix to disentangle confounding factors for the estimation of genetic variance components of complex traits

  Model 1 Model 1-ua Model 1-fb Model 2 Model 3 Model 4
f 2 0.1 0.22 N/A 0.06 0.05 0.04
  (0.07) (0.03)   (0.02) (0.02) (0.02)
c 2 0.11 0.11 0.12 0.08 0.08 0.06
  (0.02) (0.02) (0.02) (0.02) (0.02) (0.02)
u 2 0.25 N/A 0.46 N/A N/A N/A
  (0.15)   (0.07)    
g 2 N/A N/A N/A 0.50 0.36 0.29
     (0.04) (0.08) (0.08)
α 2 N/A N/A N/A N/A 0.18 0.20
      (0.16) (0.17)
δ 2 N/A N/A N/A N/A N/A 0.15
       (0.14)
Log L 1604.08 1602.37 1602.88 1670.71 1717.3c 1730.33d
      (5.26) (14.72)
Parameters f, c, u f, c c, u f, c, g f, c, g, α f, c, g, α, δ
AICe -3202.16 -3200.74 -3201.76 -3334.20 -3418.08 -3425.22
  1. Proportion of total phenotypic variance due to family (f), cage (c), and polygenic effects based on pedigree (u), realized relationships (g), and specific additive and dominance SNP effects (α and δ) when using model 1, 2, 3 and 4 for REP
  2. cThe averaged log-likelihood during MCMC process (the averaged number of parameters due to additive SNP in the model)
  3. dThe averaged log-likelihood during MCMC process (the averaged number of parameters due to additive and dominance SNP in the model)