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Table 1 Simulated data: performance assessment for two different scenarios, characterized by different values of the dispersion parameter ψ

From: An integrative Bayesian Dirichlet-multinomial regression model for the analysis of taxonomic abundances in microbiome data

  Overall Taxa
  DMBVS MAPBL C&L CORTEST DMBVS MAPBL C&L CORTEST
ψ=0.01         
MCC 0.93 0.64 0.67 0.73 0.89 0.66 0.50 0.85
FNR 0.05 0.10 0.12 0.31 0.00 0.46 0.43 0.02
FPR 0.00 0.01 0.01 0.00 0.05 0.01 0.09 0.06
Accuracy 1.00 0.99 0.99 1.00 0.96 0.91 0.85 0.95
ψ=0.1         
MCC 0.72 0.42 0.54 0.56 0.73 0.40 0.38 0.70
FNR 0.39 0.58 0.28 0.63 0.24 0.73 0.52 0.37
FPR 0.00 0.01 0.01 0.00 0.05 0.01 0.12 0.02
Accuracy 1.00 0.99 0.99 1.00 0.92 0.86 0.81 0.92
  1. Values are rounded averages over thirty replicates. Results for Matthews’ Correlation Coefficient, Falso Positive Rate, False Negative Rate, and Accuracy, are based on the median probability model. DMBVS: Dirichlet–Multinomial Bayesian Variable Selection (our method), MAPBL: Maximum A Posteriori Bayesian Lasso, C&L: composite penalty from Chen and Li (2013), CORTEST: Multiplicity Corrected Correlation Tests as in Wu et al. (2010)
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