generateFBMNetwork: Generate Fundamental Boolean Model type of Network

In clsdavid/FBNNet2_public: Fundamental Boolean Model and Networks

Generate Fundamental Boolean Model type of Network

Description

This is the main entry of the package FBNNet that can be used to mine the gene regulatory network.

Usage

generateFBMNetwork(
  timeseries_data,
  method = c("kmeans", "edgeDetector", "scanStatistic"),
  maxK = 4,
  useParallel = FALSE,
  max_deep_temporal = 1,
  threshold_confidence = 1,
  threshold_error = 0,
  threshold_support = 1e-05,
  maxFBNRules = 5,
  network_only = TRUE,
  verbose = FALSE
)

Arguments

timeseries_data	A list of timeseries data of samples.
method	Specify a method to discrete the data in the range of ('kmeans', 'edgeDetector', 'scanStatistic') for the function BoolNet::binarizeTimeSeries to convert the data from numeric value to boolean value.
maxK	The maximum deep of the Orchard Cube can mine into.
useParallel	Optional, by default it is FALSE not to run the network inference algorithm in parallel. FALSE without parallel
max_deep_temporal,	a setting for Temporal Fundamental Boolean model that specifies the maximum temporal space
threshold_confidence	A threshold of confidence (between 0 and 1) that used to filter the Fundamental Boolean functions
threshold_error	A threshold of error rate (between 0 and 1) that used to filter the Fundamental Boolean functions
threshold_support	A threshold of support (between 0 and 1) that used to filter the Fundamental Boolean functions
maxFBNRules	The maximum rules per type (Activation and Inhibition) per gene can be mined, the rest will be discarded
network_only	Optional for Debug purpose, if TRUE, only output the networks only, otherwise, output the Orchard cube as well. Warning, turn off this may cause memory leaking if the number of nodes is too large.
verbose	Optional, if it is TRUE, then output the logger information to the console.

Value

An object of a list contains Fundamental Boolean Network and Orchard cube (optional) if network_only set to FALSE.

Author(s)

Leshi Chen, leshi, [e-mail], [e-mail]

References

Chen et al.(2018), Front. Physiol., 25 September 2018, (Front. Physiol.)

Mussel, Hopfensitz et al. 2010, BoolNet - an R package for generation, reconstruction and analysis of Boolean networks

Examples

 
data('yeastTimeSeries')

network <- generateFBMNetwork(yeastTimeSeries, verbose = TRUE)
network
## draw the general graph
FBNNetwork.Graph(network)

## get the Orchard cube as well as networks
res <- generateFBMNetwork(yeastTimeSeries, network_only = FALSE)
res

clsdavid/FBNNet2_public documentation built on April 20, 2023, 4:36 p.m.