Table 2

Analysis of Variance for Network Analysis of Bay-0 Versus Sha.

Sourcea

DFb

SSc

F Valued

Pr > Fe


Model

739

8796.0

81.70

< .0001

Error

220

32.0

Total

959

8828.1


R-Square

Coeffient of Variation (%)

0.996369

4.009452

Source

DF

Type III SS

F Value

Pr > F


NETWORK

19

4028.9

1455.4

< .0001

GENE(NETWORK)

220

4435.0

138.4

< .0001

ACCESSION

1

0.2

1.8

0.1816

REPLICATE

1

0.1

1.2

0.2688

NETWORK × ACCESSION

19

15.7

5.7

< .0001

GENE(NETWORK) × ACCESSION

220

259.6

8.1

< .0001

ACCESSION × REPLICATE

1

0.2

1.2

0.2719

NETWORK × REPLICATE

19

4.3

1.6

0.0667

GENE(NETWORK) × REPLICATE

220

49.2

1.5

0.0008

NETWORK × ACCESSION × REPLICATE

19

3.1

1.1

0.3409


a Source of Variation in linear additive model.

b DF = degrees of freedom.

c SS = Sums of squares obtained from ANOVA.

d F Value obtained from ANOVA.

e Pr > F = the probability that the F value is equal to the value shown. A probability less than 0.05 indicates that the F value is significant.

Kliebenstein et al. BMC Bioinformatics 2006 7:308   doi:10.1186/1471-2105-7-308

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