R: Routines for the functional analysis of biological networks

# Routines for the functional analysis of biological networks

## Documentation for package ‘BioNet’ version 1.73.0

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

BioNet-package | Routines for the functional analysis of biological networks
aggrPvals | Aggregate several p-values into one p-value
BioNet | Routines for the functional analysis of biological networks
bumOptim | Fitting a beta-uniform mixture model to p-value distribution
compareNetworks | Compare parameters of two networks
consensusScores | Calculation of a consensus score for a network
fbum | Compute the density of the bum distribution
fbumLL | Calculate log likelihood of BUM model
fdrThreshold | Calculate p-value threshold for given FDR
fitBumModel | Fit beta-uniform mixture model to a p-value distribution
getCompScores | Partition scores for subgraphs of the network
getEdgeList | Get representation of graph as edgelist
hist.bum | Histogram of the p-value distribution with the fitted bum model
largestComp | Extract largest component of network
largestScoreComp | Component with largest score
loadNetwork.sif | Load network from Cytoscape sif file
loadNetwork.tab | Load network from tabular format
makeNetwork | Create graph from source and target vectors
mapByVar | Select probeset by variance and get PPI ID
permutateNodes | Permute node labels
piUpper | Upper bound pi for the fraction of noise
plot.bum | Quantile-quantile plot for the beta-uniform mixture model
plot3dModule | 3D plot of the network
plotLLSurface | Log likelihood surface plot
plotModule | Plot of the network
print.bum | Print information about bum model
pvaluesExample | Example p-values for aggregation statistics
readHeinzGraph | Convert HEINZ output to graph
readHeinzTree | Convert HEINZ output to tree
resamplingPvalues | Resampling of microarray expression values and test for differential expression.
rmSelfLoops | Remove self-loops in a graph
runFastHeinz | Calculate heuristically maximum scoring subnetwork
runHeinz | Start HEINZ
save3dModule | Save a 3D plot of the network
saveNetwork | Save undirected network in various formats
scanFDR | Dataframe of scores over a given range of FDRs
scoreFunction | Scoring function for p-values
scoreNodes | Score the nodes of a network
scoreOffset | Change score offset for 2 FDRs
sortedEdgeList | Get a sorted edgelist
subNetwork | Create a subGraph
summary.bum | Print summary of informations about bum model
writeHeinz | Write input files for HEINZ
writeHeinzEdges | Write edge input file for HEINZ
writeHeinzNodes | Write node input file for HEINZ