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Table 3 Results for the simulation study for the case of having common CNVs

From: Bayesian model to detect phenotype-specific genes for copy number data

     

Bayesian Shared Model

    

Multinomial

Posterior

Normal

Posterior

 

# SNPs

χ 2

K-W

regression

Distribution

Approximation

Probability

high risk scenario (OR=2.0)

    

TPR

2000

100.00

0

100.00

100.00

100.00

100.00

TNR

2000

100.00

100.00

100.00

99.98

99.99

99.96

TPR

500

100.00

0

100.00

100.00

100.00

100.00

TNR

500

99.73

100.00

99.73

99.99

99.95

99.80

moderate risk scenario (OR=1.5)

    

TPR

2000

60.25

0

56.75

75.25

75.50

75.00

TNR

2000

99.95

100.00

99.95

99.98

99.99

99.95

TPR

500

69.25

0

67.50

96.25

96.25

95.75

TNR

500

99.81

100.00

99.81

99.96

99.99

99.98

low risk scenario (OR=1.2)

    

TPR

2000

0.75

0

0.75

10.50

10.25

10.25

TNR

2000

99.99

100

99.9

100.00

100.00

99.98

TPR

500

1.50

0

3.25

25.25

26.50

25.50

TNR

500

99.99

100

99.99

99.99

99.99

99.98

  1. Results for the simulation described in Simulation Studies Section for the case of having common CNVs with major allele frequency simulated from U(0.01, 0.1). The different scenarios are described in that section. We compare four different approaches: χ2 test, Kruskall-Wallis (K-W), Multinomial regression using likelihood ratio test, and our proposed Bayesian model. The comparison was based on computing the True Positive and Negative Rates, TPR and TNR respectively. Results are expressed in %.