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Table 3 Simulation study.

From: Time-course analysis of genome-wide gene expression data from hormone-responsive human breast cancer cells

 

Noise model N

Noise model T5

Noise model T3

Method

Rej.4

Corr.5

FDR6

FNR7

Rej.4

Corr.5

FDR6

FNR7

Rej.4

Corr.5

FDR6

FNR7

EDGE1 0.01

928.4

921.8

0.007

0.119

953.4

948

0.006

0.1163

1054.6

1048.2

0.006

0.106

EDGE1 0.001

519.6

519.6

0.000

0.156

526

526

0.000

0.1556

544.6

544.6

0.000

0.154

timecourse 2

1386

1380

0.004

0.072

1396

1319

0.055

0.0791

1461

1384

0.052

0.072

BATS3 N, 9

1385.8

1385.8

0.000

0.071

1395.8

1391

0.003

0.0708

1460.6

1435

0.018

0.066

BATS3 N, 12

1382

1382

0.000

0.072

1393.4

1388.6

0.003

0.0710

1459.6

1433

0.018

0.066

BATS3 D, 9

1386

1386

0.000

0.071

1407.2

1403.4

0.003

0.0694

1510.2

1477.4

0.022

0.062

BATS3 D, 12

1368.2

1368.2

0.000

0.073

1384.2

1380.4

0.003

0.0719

1489.8

1457

0.022

0.064

  1. 1q-value threshold.
  2. 2Number of rejected chosen equal to the case of BATS (N,9), for comparison purpose.
  3. 3Error model N = normal, D = double-exponential, the indicated number is the value of λ.
  4. 4Rej. (Rejected) = average number of genes declared differentially expressed.
  5. 5Corr. (Correct) = average number of the correctly rejected hypotheses.
  6. 6FDR (False Discovery Rate) = average proportion of falsely rejected hypotheses over the total number of rejected hypotheses.
  7. 7FNR (False Negative Rate) = average proportion of false negatives over the total number of not rejected hypotheses.
Datasets generated with 2000 true signals, with three different noise models. Results were averaged over 5 datasets.
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BMC Bioinformatics

ISSN: 1471-2105

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