Package: CellNOptR 1.59.0

Attila Gabor

CellNOptR: Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data

This package does optimisation of boolean logic networks of signalling pathways based on a previous knowledge network and a set of data upon perturbation of the nodes in the network.

Authors:Thomas Cokelaer [aut], Federica Eduati [aut], Aidan MacNamara [aut], S Schrier [ctb], Camille Terfve [aut], Enio Gjerga [ctb], Attila Gabor [cre]

CellNOptR_1.59.0.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
CellNOptR/json (API)

# Install 'CellNOptR' in R:

install.packages('CellNOptR', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

cnodata - Get data from a CellNOpt data repository
CNOlistDREAM - Data used for the DREAM3 challenge
CNOlistToy - Toy data
CNOlistToy2 - Toy data with 2 time points
DreamModel - Model used for the DREAM3 challenge
pknmodel - Pknmodel
ToyModel - Toy model
ToyModel2 - Toy model

On BioConductor:CellNOptR-1.59.0(bioc 3.24)CellNOptR-1.58.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cellbasedassays cellbiology proteomics pathways network timecourse immunooncology

6.78 score 6 packages 168 scripts 25 mentions 81 exports 54 dependencies

Last updated from:bd7ff69ddb. Checks:1 WARNING, 10 NOTE, 2 OK, 1 ERROR. Indexed: yes.

Target	Result	Time
bioc-checks	WARNING	183
linux-devel-arm64	NOTE	212
linux-devel-x86_64	NOTE	290
source / vignettes	OK	231
linux-release-arm64	NOTE	242
linux-release-x86_64	NOTE	286
macos-release-arm64	NOTE	153
macos-release-x86_64	NOTE	479
macos-oldrel-arm64	NOTE	178
macos-oldrel-x86_64	NOTE	342
windows-devel	NOTE	224
windows-release	NOTE	287
windows-oldrel	ERROR	187
wasm-release	OK	299

Exports:buildBitString checkSignals CNOdata CNOlist CNORbool CNORwrap compatCNOlist compressModel computeScoreT1 computeScoreTN crossInhibitedData crossvalidateBoolean cutAndPlot cutAndPlotResultsT1 cutAndPlotResultsTN cutCNOlist cutModel cutNONC cutSimList defaultParameters exhaustive expandGates findNONC gaBinaryT1 gaBinaryTN getCues getFit getInhibitors getSignals getStimuli getTimepoints getVariances graph2sif ilpBinaryT1 ilpBinaryT2 ilpBinaryTN indexFinder makeCNOlist mapBack model2igraph model2sif normaliseCNOlist plot plotCNOlist plotCNOlist2 plotCNOlistLarge plotCNOlistLargePDF plotCNOlistPDF plotFit plotModel plotOptimResults plotOptimResultsPan plotOptimResultsPDF prep4sim prep4Sim preprocessing randomize randomizeCNOlist readBND readBNET readErrors readMIDAS readSBMLQual readSif readSIF residualError setSignals<-sif2graph simulateT1 simulateTN simulatorT0 simulatorT1 simulatorTN toSBML writeDot writeErrors writeMIDAS writeNetwork writeReport writeScaffold writeSIF

Dependencies:base64enc BH BiocGenerics bitops bslib cachem cli cpp11 digest evaluate farver fastmap fontawesome fs generics ggplot2 glue graph gtable highr htmltools igraph isoband jquerylib jsonlite knitr labeling lattice lifecycle magrittr Matrix memoise mime pkgconfig R6 rappdirs RBGL RColorBrewer RCurl Rgraphviz rlang rmarkdown S7 sass scales stringi stringr tinytex vctrs viridisLite withr xfun XML yaml

Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data with CellNOptR

Rendered fromCellNOptR-vignette.Rmdusingknitr::rmarkdown

Last update: 2022-03-22
Started: 2022-03-16

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
R version of CellNOptR, boolean features	CellNOptR-package CellNOptR
Build a SIF table from a logic rule written in a string	build_sif_table_from_rule
Check the CNOlist and model matching	checkSignals
Get data from a CellNOpt data repository	CNOdata cnodata
Class '"CNOlist"'	CNOlist CNOlist-class compatCNOlist,CNOlist-method getCues,CNOlist-method getInhibitors,CNOlist-method getSignals,CNOlist-method getStimuli,CNOlist-method getTimepoints,CNOlist-method getVariances,CNOlist-method length,CNOlist-method plot,CNOlist,CNOlist-method randomize,CNOlist-method readErrors,CNOlist-method setSignals<-,CNOlist-method writeErrors,CNOlist-method
List of CNOlist-class methods	CNOlist-methods compatCNOlist compatCNOlist,CNOlist getCues getCues,CNOlist getInhibitors getInhibitors,CNOlist getSignals getSignals,CNOlist getStimuli getStimuli,CNOlist getTimepoints getTimepoints,CNOlist getVariances getVariances,CNOlist getVariances,CNOlist,CNOlist-method length length,CNOlist length,CNOlist,ANY-method plot,CNOlist,CNOlist,CNOlist-method randomize randomize,CNOlist randomize,CNOlist,CNOlist-method readErrors readErrors,CNOlist setSignals<- setSignals<-,CNOlist setSignals<-,CNOlist,CNOlist-method writeErrors writeErrors,CNOlist
Data used for the DREAM3 challenge	CNOlistDREAM
Toy data	CNOlistToy
Toy data with 2 time points	CNOlistToy2
Simple Boolean analysis standalone	CNORbool
CNOR analysis wrapper	CNORwrap
Compress a model	compressModel
Compute the score of a model/data set using a bitString to cut the model.	computeScoreT1
Compute the score at TN of a model/data set using a bitString to cut the model.	computeScoreTN
Defining the set of binary variables for the ILP implementation of CellNOptR.	create_binaries
Creating and running the ILP problem.	createAndRunILP
Reading the optimal solutions as bitstrings.	createILPBitstringAll
If an inhibitor is also a measured species, replace the data with NA (when inhibited)	crossInhibitedData
k-fold crossvalidation for Boolean model.	crossvalidateBoolean
Interface to cutAndPlotResults functions.	cutAndPlot
Plot the results of an optimisation at t1	cutAndPlotResultsT1
Plot the results of an optimisation at tN	cutAndPlotResultsTN
Cut a CNOlist structure according to a model	cutCNOlist
Cut a model structure according to a bitstring	cutModel
Cuts the non-observable/non-controllable species from the model	cutNONC
Cut a simList structure according to a bitstring	cutSimList
Create a list of default parameters	defaultParameters
Exhaustive search over the optimisation of a PKN model on MIDAS data.	exhaustive
Expand the gates of a model	expandGates
Find the indexes of the non-observable and non controllable species	findNONC
Genetic algorithm used to optimise a model	gaBinaryT1
Genetic algorithm for time point N	gaBinaryTN
Compute the score of a model	getFit
Convert graph to SIF	graph2sif
ILP method used to optimise a model	ilpBinaryT1
ILP method used to optimise a model	ilpBinaryT2
ILP method used to optimise a model	ilpBinaryTN
Finds the indices, in the model fields, of the species that are measured/inhibited/stimulated	indexFinder
List of CellNOptR internal functions.	internals
Solving the ILP problem with CPLEX.	invokeCPLEX
Model used for the DREAM3 challenge	DreamModel
Make a CNOlist structure	makeCNOlist
Map an optimised model back onto the PKN model.	mapBack
Convert a model object to a igraph object	model2igraph
Convert a model object in sif format	model2sif
Normalisation for boolean modelling.	normaliseCNOlist
pknmodel	pknmodel
plot a '"CNOlist"' object - methods	plot,CNOlist,ANY-method plot.CNOlist
Plot the data in a CNOlist	plotCNOlist
Another version of plotCNOlist that allows to plot 2 cnolist in the same layout to compare them. This function uses ggplot2 library. It is recommended for small data sets (about 15 species).	plotCNOlist2
Plot the data in a CNOlist, for lists with many conditions.	plotCNOlistLarge
Plots a CNOlist into a pdf file, for lists with many conditions.	plotCNOlistLargePDF
Plots a CNOlist into a pdf file.	plotCNOlistPDF
Plot the evolution of an optimisation	plotFit
Plot a model	plotModel
Plot the data and simulated values	plotOptimResults
Plots the data and simulated values from any CellNOptR formalism	plotOptimResultsPan
Plot the data and simulated values in a pdf file	plotOptimResultsPDF
Prepare a model for simulation	prep4Sim prep4sim
Performs the pre-processing steps	preprocessing
add noise to the data contained in a CNOlist.	randomizeCNOlist
Read network from BND file	readBND
Read network from BNET file	readBNET
Reads in a CSV MIDAS file	readMIDAS readMidas
Read a SBMLQual document and returns a SIF object (as returned by readSIG	readSBMLQual
Read a SIF file and create a model object	readSIF readSif
Compute the residual error for a dataset	residualError
Convert sif to graph	sif2graph
Cut and simulation of a boolean model at t1	simulateTN
Simulation of a boolean model	simulatorT0
Simulation of a boolean model	simulatorT1
Simulation of a boolean model at any time points dependent on a previous one.	simulatorTN
Export the network to SBML-qual format	toSBML
Toy model	ToyModel
Toy model	ToyModel2
Writing the set of boundaries for each integer variable for the ILP implementation of CellNOptR.	write_bounds
Writing the set of constraints for the ILP implementation of CellNOptR.	write_constraints
Write a model, and attached features, to a dot file	writeDot
Writing the ILP problem.	writeFile
Write a CNOlist structure into a MIDAS file	writeMIDAS
Write a previous knowledge network model to a sif file (with attribute files), as well as a dot file	writeNetwork
Writing the objective function for the ILP implementation of CellNOptR.	writeObjectiveFunction
Write a report of a CellNOptR analysis	writeReport
Writes the scaffold network to a sif file (with attributes) and to a dot file	writeScaffold
Convert a model into a SIF format and save the result in a file.	writeSIF writeSif