signalOnNetwork: Quantify network connectivity by calculating signal strength...
In Amy3100/receptor2tfDiffusion: This package calculate single-sample network connectivity
Description
Usage
Arguments
Examples
Description
Quantify network connectivity by calculating signal strength between receptors and TFs.
Usage
1
signalOnNetwork(network, outputNode, inputNode, inputSignal = 0.99, n = 2000)
Arguments
network
output from initilizeNetwork list with 'network' and 'signal' components
outputNode
output node
inputNode
input node containing receptors in the signalling network
inputSignal
minimum amount of signal placed as input for signal propagation
n
number of iteration
nodeW
weight on the network node
Examples
1
2
3
4
#data(diffusionData)
#network <- initializeSignallingNetwork(network = network, nodeW = nodeW)
#signalNet<- signalOnNetwork(diffusionData$network, nodeW=M[,1], outputNode = 'FLI1',inputNode = 'TNFRSF1B', inputSignal = 0.99,n = 2000)
#{ ... }
Amy3100/receptor2tfDiffusion documentation built on Dec. 17, 2021, 8:47 a.m.
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Description Usage Arguments Examples
Description
Quantify network connectivity by calculating signal strength between receptors and TFs.
Usage
1 | signalOnNetwork(network, outputNode, inputNode, inputSignal = 0.99, n = 2000)
|
Arguments
network |
output from initilizeNetwork list with 'network' and 'signal' components |
outputNode |
output node |
inputNode |
input node containing receptors in the signalling network |
inputSignal |
minimum amount of signal placed as input for signal propagation |
n |
number of iteration |
nodeW |
weight on the network node |
Examples
1 2 3 4 | #data(diffusionData)
#network <- initializeSignallingNetwork(network = network, nodeW = nodeW)
#signalNet<- signalOnNetwork(diffusionData$network, nodeW=M[,1], outputNode = 'FLI1',inputNode = 'TNFRSF1B', inputSignal = 0.99,n = 2000)
#{ ... }
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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