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Table 2 Average (SD) of marker and QTL related statistics of the simulated population presenting low LD

From: Assessing the value of phenotypic information from non-genotyped animals for QTL mapping of complex traits in real and simulated populations

Method/Scenarioa Pvar_topMRKw(%)b Pvar_1stMRKw(%)c NtrueQTLd
Bayes C (π = 0.99) 3.95 (0.58) 0.42 (0.10) 1.40 (0.97)
Bayes C (π = 0.999) 36.71 (12.35) 12.39 (11.93) 1.80 (1.62)
WssGBLUP/SIw1 2.73 (0.53) 0.25 (0.08) 2.00 (1.70)
WssGBLUP/SIw2 10.58 (1.59) 1.45 (0.37) 2.10 (1.29)
WssGBLUP/SIw3 26.80 (4.93) 4.51 (1.31) 1.20 (0.63)
WssGBLUP/SIIw1 2.82 (0.35) 0.26 (0.04) 1.90 (1.20)
WssGBLUP/SIIw2 12.05 (1.72) 1.69 (0.38) 1.90 (1.10)
WssGBLUP/SIIw3 31.60 (3.76) 5.66 (2.49) 1.10 (0.88)
True values Pvar_topQTL(%)b Pvar_1stQTL (%)c topQTLd
24.32 (4.92) 3.19 (0.61) 15.4 (2.32)
  1. The averages are expressed over the ten replicates, using the Bayes C and weighted single step GBLUP (WssGBLUP) analyses
  2. aGWAS using (SI) or ignoring (SII) phenotypic information of non-genotyped animals, applying different weights (w1, w2 and w3) for the SNP effects in the WssGBLUP method. And using π = 0.99 and π = 0.999 in the Bayes C method
  3. bGenetic variance (%) explained by the sum of variances accounted by top marker windows (Pvar_topMRKw) and by the NtopQTLs (Pvar_topQTL)
  4. cMaximum genetic variance (%) explained by a top marker window (Pvar_1stMRKw) and by a topQTL (Pvar_1stQTL)
  5. dEstimated number of true QTLs explaining 1 % or more of the genetic variance (NtopQTL), and number of NtopQTLs identified by a top marker window distant no more than 1 Mb from a NtopQTL (NtrueQTL)