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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