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Table 6 Performance statistics of selected genes on NSCLC RNA-seq data (stage segmentation)

From: Weighted-SAMGSR: combining significance analysis of microarray-gene set reduction algorithm with pathway topology-based weights to select relevant genes

 

Training set (10-fold CV results)

Test set

Method (n)

Error (%)

GBS

BCM

AUPR

Error (%)

GBS

BCM

AUPR

SAMGSR (9)

35.2

0.242

0.539

0. 575

50

0.279

0.507

0.531

W-SAMGSR (8)

32.8

0.231

0.556

0.584

49.3

0.276

0.513

0.580

LASSO (30)

36

0.219

0.558

0.610

50

0.453

0.500

0.509

Penalized SVM (34)

36.8

0.255

0.562

0.603

50

0.329

0.501

0.518

gelnet (252)

36.8

0.231

0.517

0.547

50

0.465

0.499

0.475

RRFE (93)

35.2

0.185

0.545

0.578

50

0.471

0.500

0.506

  1. Note: W-SAMGSR weighted-SAMGSR, gelnet generalized elastic net, RRFE reweighted recursive feature elimination
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Biology Direct

ISSN: 1745-6150

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