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Table 2 Simulation results

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

  Training set Test set
Method (Sizea) HDAC1 (%) GNAS (%) Error (%) GBS BMC AUPR
A. Simulated from 60 independent normal-distributed random variables
 SAMGSR (3.8) 19 100 16.5 0.118 0.733 0.921
 W-SAMGSR (6.23) 65 100 13.2 0.101 0.755 0.948
B. Simulated based on the NSCLC microarray data
 SAMGSR (3.94) 0 100 44.5 0.256 0.517 0.550
 W-SAMGSR (6.28) 77 100 40.5 0.241 0.534 0.621
  1. Note: W-SAMGSR stands for weighted-SAMGSR
  2. astands for average the number of genes selected by either SAMGSR or W-SAMGSR over 100 replicates