Skip to main content

Table 2 Operating characteristics for Latin Square dataset

From: A Bayesian calibration model for combining different pre-processing methods in Affymetrix chips

  First 64 ranked probesets
  FP (%) TN (%) TP (%) FN (%)
Combined 12 (0.1) 10545 (99.9) 52 (81.3) 12 (18.7)
MAS5 23 (0.2) 10534 (99.8) 41 (64.1) 23 (35.9)
RMA 14 (0.1) 10543 (99.9) 50 (78.1) 14 (21.9)
dChip 31 (0.4) 10526 (99.6) 33 (51.6) 31 (48.4)
  1. The table presents the operating characteristics of the combined method and of each pre-processing method on the first 64 probesets ranked accordingly to their tail posterior probability. The combined strategy is more able to recognize true positives and true negatives than each single method. Note that FP = FN since the size of the list of differentially expressed probesets is equal to the number of true positives.