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BioNet (version 1.32.0)

Routines for the functional analysis of biological networks

Description

This package provides functions for the integrated analysis of protein-protein interaction networks and the detection of functional modules. Different datasets can be integrated into the network by assigning p-values of statistical tests to the nodes of the network. E.g. p-values obtained from the differential expression of the genes from an Affymetrix array are assigned to the nodes of the network. By fitting a beta-uniform mixture model and calculating scores from the p-values, overall scores of network regions can be calculated and an integer linear programming algorithm identifies the maximum scoring subnetwork.

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Version

Version

1.32.0

License

GPL (>= 2)

Maintainer

Marcus Dittrich

Last Published

February 15th, 2017

Functions in BioNet (1.32.0)

makeNetwork

Create graph from source and target vectors
rmSelfLoops

Remove self-loops in a graph
consensusScores

Calculation of a consensus score for a network
readHeinzTree

Convert HEINZ output to tree
hist.bum

Histogram of the p-value distribution with the fitted bum model
scanFDR

Dataframe of scores over a given range of FDRs
sortedEdgeList

Get a sorted edgelist
runHeinz

Start HEINZ
resamplingPvalues

Resampling of microarray expression values and test for differential expression.
largestScoreComp

Component with largest score
readHeinzGraph

Convert HEINZ output to graph
save3dModule

Save a 3D plot of the network
BioNet-package

Routines for the functional analysis of biological networks
aggrPvals

Aggregate several p-values into one p-value
compareNetworks

Compare parameters of two networks
loadNetwork.sif

Load network from Cytoscape sif file
print.bum

Print information about bum model
scoreFunction

Scoring function for p-values
mapByVar

Select probeset by variance and get PPI ID
fdrThreshold

Calculate p-value threshold for given FDR
largestComp

Extract largest component of network
writeHeinzNodes

Write node input file for HEINZ
bumOptim

Fitting a beta-uniform mixture model to p-value distribution
scoreOffset

Change score offset for 2 FDRs
writeHeinz

Write input files for HEINZ
getCompScores

Partition scores for subgraphs of the network
fbum

Compute the density of the bum distribution
writeHeinzEdges

Write edge input file for HEINZ
saveNetwork

Save undirected network in various formats
summary.bum

Print summary of informations about bum model
loadNetwork.tab

Load network from tabular format
fitBumModel

Fit beta-uniform mixture model to a p-value distribution
getEdgeList

Get representation of graph as edgelist
pvaluesExample

Example p-values for aggregation statistics
plot3dModule

3D plot of the network
plotLLSurface

Log likelihood surface plot
fbumLL

Calculate log likelihood of BUM model
plotModule

Plot of the network
scoreNodes

Score the nodes of a network
permutateNodes

Permute node labels
subNetwork

Create a subGraph
plot.bum

Quantile-quantile plot for the beta-uniform mixture model
piUpper

Upper bound pi for the fraction of noise
runFastHeinz

Calculate heuristically maximum scoring subnetwork