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Table 1 Comparison of performance in terms of FDR, mdFDR, TPR, TPR_hypo and TPR_hyper of four procedures (logistic regression, DSS, z-test and the proposed Bayesian) at different γ values for the first set of simulation studies (without subject effect). Results are averaged over 100 replications of 20,000 CpG loci with two samples under each condition

From: A full Bayesian partition model for identifying hypo- and hyper-methylated loci from single nucleotide resolution sequencing data

  

Logistic

DSS

z-test

Bayesian

  

regression

   

γ=0.01

FDR

0.0043

0.0001

0.0055

0.0091

 

mdFDR

0.0048

0.0001

0.0059

0.0109

 

TPR

0.2156

0.0837

0.2027

0.2548

 

TPR_hypo

0.2162

0.0752

0.2129

0.2596

 

TPR_hyper

0.2145

0.0952

0.1889

0.2471

γ=0.05

FDR

0.0158

0.0003

0.0182

0.0184

 

mdFDR

0.0159

0.0003

0.0183

0.0188

 

TPR

0.3861

0.1672

0.3528

0.4099

 

TPR_hypo

0.3921

0.159

0.3694

0.4251

 

TPR_hyper

0.3787

0.1772

0.3326

0.3912

γ=0.1

FDR

0.0207

0.0005

0.0244

0.0216

 

mdFDR

0.0207

0.0005

0.0244

0.0216

 

TPR

0.5398

0.2934

0.4964

0.5775

 

TPR_hypo

0.5379

0.2851

0.5011

0.5879

 

TPR_hyper

0.542

0.3032

0.4909

0.5652

γ=0.15

FDR

0.0208

0.0005

0.0251

0.0217

 

mdFDR

0.0208

0.0005

0.0251

0.0217

 

TPR

0.6691

0.4345

0.6307

0.7161

 

TPR_hypo

0.6619

0.422

0.627

0.7201

 

TPR_hyper

0.6779

0.4497

0.6353

0.7113

γ=0.2

FDR

0.02

0.0006

0.0257

0.0214

 

mdFDR

0.02

0.0006

0.0257

0.0214

 

TPR

0.7769

0.5751

0.7476

0.8214

 

TPR_hypo

0.7708

0.5628

0.7422

0.8253

 

TPR_hyper

0.7848

0.591

0.7546

0.8163