Regression-based network inference using Bayesian Model Averaging

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Documentation for package ‘networkBMA’ version 2.22.0

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brem.data The subsets of the yeast-rapamycin time-series data from Yeung et al. (2011) and Lo et al. (2011), and of the static yeast gene-expression data from Brem et al. (2002, 2005), that are used in the 'networkBMA' package vignette.
contabs Contingency tables for networks with probabilistic edges.
contabs.netwBMA Network assessment with incomplete context.
contabs.prelim Preliminary calculation for network assessment.
dream4gold10 DREAM 4 (Stolovitsky et al. 2007) 'gold standard' reference network specifications, simulated time series perturbation subsets, and steady state (wild-type) gene expression levels.
dream4gold100 DREAM 4 (Stolovitsky et al. 2007) 'gold standard' reference network specifications, simulated time series perturbation subsets, and steady state (wild-type) gene expression levels.
dream4ts10 DREAM 4 (Stolovitsky et al. 2007) 'gold standard' reference network specifications, simulated time series perturbation subsets, and steady state (wild-type) gene expression levels.
dream4ts100 DREAM 4 (Stolovitsky et al. 2007) 'gold standard' reference network specifications, simulated time series perturbation subsets, and steady state (wild-type) gene expression levels.
dream4wild10 DREAM 4 (Stolovitsky et al. 2007) 'gold standard' reference network specifications, simulated time series perturbation subsets, and steady state (wild-type) gene expression levels.
dream4wild100 DREAM 4 (Stolovitsky et al. 2007) 'gold standard' reference network specifications, simulated time series perturbation subsets, and steady state (wild-type) gene expression levels.
fastBMAcontrol Control parameters for 'networkBMA' when using fastBMA algorithm
fastgControl Control parameters for using Zellner's g-prior in fastBMA algorithm in 'networkBMA'
gControl Control parameters for using Zellner's g-prior in 'ScanBMA'
iBMAcontrolLM Control parameters for 'iterateBMAlm'
iterateBMAlm Iterative BMA for linear modeling with prior variable probabilities.
matrixFormat Contingency tables for networks with probabilistic edges.
networkBMA Gene network inference from time series data via BMA.
prc Receiver Operating Characteristic and Precision-Recall Curves
referencePairs The subsets of the yeast-rapamycin time-series data from Yeung et al. (2011) and Lo et al. (2011), and of the static yeast gene-expression data from Brem et al. (2002, 2005), that are used in the 'networkBMA' package vignette.
reg.known The subsets of the yeast-rapamycin time-series data from Yeung et al. (2011) and Lo et al. (2011), and of the static yeast gene-expression data from Brem et al. (2002, 2005), that are used in the 'networkBMA' package vignette.
reg.prob The subsets of the yeast-rapamycin time-series data from Yeung et al. (2011) and Lo et al. (2011), and of the static yeast gene-expression data from Brem et al. (2002, 2005), that are used in the 'networkBMA' package vignette.
roc Receiver Operating Characteristic and Precision-Recall Curves
ScanBMA Bayesian Model Averaging for linear regression models.
ScanBMAcontrol Control parameters for 'ScanBMA'
scores Scores for assessment from contingency tables.
summary.networkBMA Summarizes a 'networkBMA' object.
timeSeries The subsets of the yeast-rapamycin time-series data from Yeung et al. (2011) and Lo et al. (2011), and of the static yeast gene-expression data from Brem et al. (2002, 2005), that are used in the 'networkBMA' package vignette.
varord Variable orderings for linear regression.
vignette The subsets of the yeast-rapamycin time-series data from Yeung et al. (2011) and Lo et al. (2011), and of the static yeast gene-expression data from Brem et al. (2002, 2005), that are used in the 'networkBMA' package vignette.
writeEdges Output network edges to text in Cytoscape-readable format.