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Table 3 Estimation of importance of different explanatory factors by Boruta analysis

From: Sequence imputation from low density single nucleotide polymorphism panel in a black poplar breeding population

Factor cProps lbProps Props
  (Mean ± SD) (Mean ± SD) (Mean ± SD)
shadowMax 1.44 ± 0.93 1.48 ± 0.70 1.80 ± 1.30
shadowMean -0.05 ± 0.79 -0.22 ± 0.52 -0.01 ± 0.82
shadowMin -2 ± 0.53 -2.22 ± 1.25 -1.57 ± 0.91
hweOri 32.96 ± 1.04 39.84 ± 0.73 40.33 ± 1.99
QUAL 98.95 ± 5.12 67.83 ± 1.70 67.90 ± 1.76
Weight 131.86 ± 3.56 92.78 ± 4.20 101.57 ± 4.23
FreqOri 64.28 ± 2.19 110.92 ± 2.79 115.02 ± 3.28
DEPTH 114.21 ± 5.08 75.51 ± 1.67 114.81 ± 4.81
RatioDensity 1,182.87 ± 39.82 36.68 ± 1.50 1,351.57 ± 43.94
  1. Boruta analyses for the different explanatory factors assumed for imputation quality variables Props, cProps and lbProps. Values correspond to averaged effects and their corresponding standard deviations allowing for a ranking of importance of the factors. The maximum value is bolded. Props: proportion of SNPs correctly imputed; cProps: proportion of SNPs correctly imputed corrected by the minor allele frequency; lbProps: lower bound proportion of SNPs correctly imputed based only on the allelic frequency; hweOri: p-value of a Hardy-Weinberg Equilibrium test for each site [47] ; Weight: LD weight estimate with the LDAK5 software; FreqOri: original allelic frequency in the sequenced individuals; QUAL: per-site SNP quality from the calling step; DEPTH: sequencing depth per site summed across all individuals ; RatioDensity: ratio between SNPchip density and SNPseq density in a 500kb window. “ShadowMean”, “shadowMax” and “ShadowMin” correspond to effects obtained by shuffling the original attributes across objects and used as a reference for deciding which factors are truly important