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Table 2 Variance components and LogLikelihood for models with or without the segment

From: Rapid screening for phenotype-genotype associations by linear transformations of genomic evaluations

Seg-chromosome 6 3 5
SNP − log 10 (p-value) 8.02 5.94 3.78
Lk_m1 −1227.938 −1227.938 −1227.938
Lk_m2 −1210.800 −1223.178 −1224.540
LRT 34.28 9.52 6.80
p-value LRT 1.1 × 10−9 6.5 × 10−4 3.1 × 10−3
VarE_m1 3.70 3.70 3.70
VarA_m1 2.68 2.68 2.68
VarE_m2 3.73 3.67 3.69
VarA_m2 1.95 2.42 2.55
segmVA 0.70 0.63 0.15
%segmVA 0.11 0.09 0.02
  1. Seg-chromosome = Number of chromosome where segment is located, m1 = model(2a) without the segment: y = Xβ + a + e, m2 = model (8) with the segment y = Xβ + a1 + a2 + e, SNP − log 10 (p-value) = −Logarithm in base 10 of the SNP p-value selected to create a segment, Lk_m1 = −LogLikelihood for m1, Lk_m2 = −LogLikelihood for m2, LRT = Likelihood Ratio Test for m1 and m2, p-value LRT  = p-value for LRT, VarE_m1 = Error variance σ e 2 of m1, VarA_m1 = Additive variance σ A 2 of m1, VarE_m2 = Error variance σ e 2 of m2, VarA_m2 = Additive variance σ A 2 of m2, segmVA = Additive variance segment σ A 1 2 of m2, %segmVa = Proportion in% of the total variance explained by the segment.