Skip to main content

Table 2 Performance of DEGnext on bio-test data (T3) of all 17 datasets using general learning considering fivefold cross validation

From: DEGnext: classification of differentially expressed genes from RNA-seq data using a convolutional neural network with transfer learning

Dataset

Accuracy

Recall

Precision

F-measure

MCC

BLCA

98.42

98.42

98.49

0.98

0.97

BRCA

98.80

98.80

98.83

0.99

0.98

 

100.00

100.00

100.00

1.00

1.00

CHOL

COAD

99.64

99.64

99.65

1.00

0.99

ESCA

97.95

97.95

98.10

0.98

0.96

HNSC

99.32

99.32

99.34

0.99

0.98

KICH

100.00

100.00

100.00

1.00

1.00

KIRC

99.78

99.78

99.78

1.00

1.00

KIRP

100.00

100.00

100.00

1.00

1.00

LIHC

95.93

95.93

96.23

0.96

0.85

LUAD

99.82

99.82

99.83

1.00

1.00

LUSC

99.88

99.88

99.88

1.00

1.00

PRAD

99.35

99.35

99.36

0.99

0.99

READ

95.39

95.39

96.54

0.95

0.92

STAD

96.89

96.89

97.06

0.97

0.93

THCA

99.87

99.87

99.87

1.00

1.00

UCEC

99.60

99.60

99.61

1.00

0.99