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Table 1 Posterior predictive model diagnostics are given for 10 randomly selected genes from adenocarcinoma TCGA samples

From: MCMC implementation of the optimal Bayesian classifier for non-Gaussian models: model-based RNA-Seq classification

Gene ID IQR ( S n ) 95% int. for IQR ( x rep) p-value
UPK1A|11045 2.12 [1.0, 3.0] 0.09
OR4P4|81300 0.00 [0.0, 0.0] 0.50
PCDHA12|56137 139.22 [107.8, 187.0] 0.54
MDS2|259283 1.85 [2.0, 5.0] 1.00
AXIN2|8313 347.69 [331.5, 439.3] 0.85
DYNLT1|6993 848.41 [830.0, 1043.3] 0.90
RARA|5914 786.43 [706.8, 881.3] 0.62
TMEM194A|23306 396.06 [367.0, 471.3] 0.76
AGPS|8540 496.45 [505.8, 636.5] 0.97
NLRP2|55655 854.47 [381.3, 677.5] 0.00
  1. Inter-quartile distance (IQR) is used as a robust measure of dispersion. In the table, IQR(S n ) is the training data’s IQR, followed by the 95-th credible interval, and the posterior predictive P-value. In cases where the P-value is close to 0 or 1, the true test statistic’s distance from the 95-th credible interval can be used to determine the magnitude of the mis-fit.