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Table 1 Number of common 1-Mb windowsa (above diagonal) and Pearson’s correlation (below diagonal) between response variables

From: Genomic regions underlying uniformity of yearling weight in Nellore cattle evaluated under different response variables

 

dEBVm

dEBVv

dEBVv_r0

ln_\( {\upsigma}_{\widehat{\mathrm{e}}}^2 \)

dEBVm

 

8

0

0

dEBVv

0.90 (0.02)

 

1

1

dEBVv_r0

0.19 (0.05)

0.53 (0.04)

 

2

ln_\( {\upsigma}_{\widehat{\mathrm{e}}}^2 \)

−0.01 (0.05)

0.08 (0.05)

0.24 (0.05)

 
  1. a Considering only the top 20 windows that explained the largest proportion of genetic variance for each response variable; dEBVm and dEBVv: deregressed EBV for mean and residual variance of yearling weight, respectively; dEBVv_r0 and ln_\( {\upsigma}_{\widehat{\mathrm{e}}}^2 \): deregressed EBV for residual variance and log-transformed variance of estimated residuals, respectively, both assuming null genetic correlation between mean and residual variance. Standard errors are presented between brackets