Table 4

Results for the simulation study for the case of having polymorphic CNVs
Bayesian Shared Model
Multinomial Posterior Normal Posterior
# SNPs χ2 K-W regression Distribution Approximation Probability
moderate risk scenario (OR=2.0)
TPR 2000 48.50 0 52.25 75.25 74.25 75.50
TNR 2000 100.00 100 100.00 100.00 100.00 100.00
TPR 500 46.25 0 42.50 64.50 64.75 64.25
TNR 500 100.00 100 100.00 100.00 100.00 100.00
moderate risk scenario (OR=1.5)
TPR 2000 30.25 0 35.45 58.50 58.50 57.75
TNR 2000 100.00 100 100.00 99.98 99.99 99.97
TPR 500 20.50 0 23.25 44.25 44.25 44.50
TNR 500 99.99 100 99.99 99.96 99.96 99.94
low risk scenario (OR=1.2)
TPR 2000 0.70 0 0.70 20.25 20.25 20.75
TNR 2000 99.98 100 99.99 99.97 99.99 99.98
TPR 500 0.50 0 0.50 16.25 16.25 15.75
TNR 500 99.99 100 99.99 99.99 99.99 99.98

Results for the simulation described in Simulation Studies Section for the case of having polymorphic 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 %.

González et al.

González et al. BMC Bioinformatics 2012 13:130   doi:10.1186/1471-2105-13-130

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