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Table 2 Top SNPs identified by the Random Forest and GRAMMAR-CG Approach for Trait 1

From: Genome wide association analysis of the 16th QTL- MAS Workshop dataset using the Random Forest machine learning approach

   

Trait 1

    

Random Forest method

  

Grammar_CG

  

Multiple Trait EBV

 

Multiple Trait EBV

 

SNPname

CHR

pos Kb

 

name

CHR

pos Kb

p-value

SNP6499

4

24.900

 

SNP6499

4

24.900

3,6E-17

SNP4688

3

34.350

 

SNP1682

1

84.050

1,2E-07

SNP4674

3

33.650

 

SNP1683

1

84.100

4,4E-06

SNP4197

3

9.800

 

SNP6498

4

24.850

7,2E-06

SNP7145

4

57.200

 

SNP3585

2

79.200

1,1E-05

SNP1012

1

50.550

 

SNP6501

4

25.000

1,1E-05

SNP1614

1

80.650

 

SNP6469

4

23.400

8,4E-05

SNP6534

4

26.650

 

SNP9362

5

68.050

9,5E-05

Single Trait EBV

 

Single trait EBV

 

SNP6499

4

24.900

 

SNP6499

4

24.900

9,8E-16

SNP4688

3

34.350

 

SNP1682

1

84.050

9,8E-06

SNP4674

3

33.650

 

SNP6501

4

25.000

1,4E-05

SNP4197

3

9.800

 

SNP6498

4

24.850

3,0E-05

SNP1012

1

50.550

 

SNP1683

1

84.100

5,0E-05

SNP1614

1

80.650

 

SNP293

1

14.600

5,6E-05

Yield Deviation

 

Yield Deviation

 

SNP6499

4

24.900

 

SNP6499

4

24.900

1,9E-19

SNP1683

1

84.100

 

SNP1682

1

84.050

4,2E-09

SNP6507

4

25.300

 

SNP1683

1

84.100

2,8E-08

SNP1614

1

80.650

 

SNP6498

4

24.850

2,7E-07

SNP6506

4

25.250

 

SNP6501

4

25.000

6,9E-07

SNP4674

3

33.650

 

SNP6506

4

25.250

3,3E-06

SNP1682

1

84.050

 

SNP293

1

14.600

9,2E-06

SNP9374

5

68.650

 

SNP6507

4

25.300

2,7E-05

SNP1012

1

50.550

 

SNP1699

1

84.900

5,1E-05

SNP1685

1

84.200

 

SNP1161

1

58.000

7,6E-05