AddIDsToVertices        add IDs to vertices
AddWeightsToEdges       add weights to edges
AnalyseExperimentalData
                        analyse experimental data
AnalysePredictionsList
                        analyse predictions list
CalculateEnrichmentPValue
                        calculates an enrichment p-value
CalculateSignificance   calculate overall significance p-value
CalculateSignificanceUsingCubicAlgorithm
                        calculate significance using the cubic
                        algorithm
CalculateSignificanceUsingCubicAlgorithm1b
                        Calculate Significance Using Cubic Algorithm
CalculateSignificanceUsingQuarticAlgorithm
                        calculate significance using the quartic
                        algorithm
CalculateTotalWeightForAllContingencyTables
                        calculate total weight for all contingency
                        tables
CalculateWeightGivenValuesInThreeByThreeContingencyTable
                        calculate weight given values in three-by-three
                        contingency table
CausalR-package         The CausalR package
CheckPossibleValuesAreValid
                        check possible values are valid
CheckRowAndColumnSumValuesAreValid
                        check row and column sum values are valid
CompareHypothesis       compare hypothesis
ComputeFinalDistribution
                        compute final distribution
ComputePValueFromDistributionTable
                        compute a p-value from the distribution table
CreateCCG               create a Computational Causal Graph (CCG)
CreateCG                create a Computational Graph (CG)
CreateNetworkFromTable
                        create network from table
DetermineInteractionTypeOfPath
                        determine interaction type of path
FindApproximateValuesThatWillMaximiseDValue
                        find approximate values that will maximise D
                        value
FindIdsOfConnectedNodesInSubgraph
                        find Ids of connected nodes in subgraph
FindMaximumDValue       find maximum D value
GetAllPossibleRoundingCombinations
                        get score for numbers of correct and incorrect
                        predictions
GetApproximateMaximumDValueFromThreeByTwoContingencyTable
                        returns approximate maximum D value or weight
                        for a 3x2 superfamily
GetApproximateMaximumDValueFromTwoByTwoContingencyTable
                        computes an approximate maximum D value or
                        weight
GetCombinationsOfCorrectandIncorrectPredictions
                        returns table of correct and incorrect
                        predictions
GetExplainedNodesOfCCG
                        Get explained nodes of CCG
GetInteractionInformation
                        returns interaction information from input data
GetMatrixOfCausalRelationships
                        compute causal relationships matrix
GetMaxDValueForAFamily
                        get maximun D value for a family
GetMaxDValueForAThreeByTwoFamily
                        get maximum D value for three-by-two a family
GetMaximumDValueFromTwoByTwoContingencyTable
                        get maximum D value from two-by-two contingency
                        table
GetNodeID               get CCG node ID
GetNodeName             get node name
GetNumberOfPositiveAndNegativeEntries
                        counts the number of positive and negative
                        entries
GetPathsInSifFormat     Get paths in Sif format
GetRegulatedNodes       get regulated nodes
GetRowAndColumnSumValues
                        get row and column sum values
GetScoreForNumbersOfCorrectandIncorrectPredictions
                        returns the score for a given number of correct
                        and incorrect predictions
GetScoresForSingleNode
                        Get scores for single node
GetScoresWeightsMatrix
                        get scores weight matrix
GetScoresWeightsMatrixByCubicAlg
                        get scores weights matrix by the cubic
                        algorithm
GetSetOfDifferentiallyExpressedGenes
                        get set of differientially expressed genes
GetSetOfSignificantPredictions
                        get set of significant predictions
GetShortestPathsFromCCG
                        get shortest paths from CCG
GetWeightForNumbersOfCorrectandIncorrectPredictions
                        get weight for numbers of correct and incorrect
                        predictions
GetWeightsAboveHypothesisScoreAndTotalWeights
                        get weights above hypothesis score and total
                        weights
GetWeightsAboveHypothesisScoreForAThreeByTwoTable
                        updates weights for contingency table and
                        produce values for p-value calculation
GetWeightsFromInteractionInformation
                        get weights from interaction information
MakePredictions         make predictions
MakePredictionsFromCCG
                        make predictions from CCG
MakePredictionsFromCG   make predictions from CG
OrderHypotheses         order hypotheses
PlotGraphWithNodeNames
                        plot graph with node names
PopulateTheThreeByThreeContingencyTable
                        populate the three-by-three contingency table
PopulateTwoByTwoContingencyTable
                        Populate Two by Two Contingency Table
ProcessExperimentalData
                        process experimental data
RankTheHypotheses       rank the hypotheses
ReadExperimentalData    read experimental data
ReadSifFileToTable      read .sif to Table
RemoveIDsNotInExperimentalData
                        remove IDs not in experimental data
ScoreHypothesis         score hypothesis
ValidateFormatOfDataTable
                        validate format of the experimental data table
ValidateFormatOfTable   validate format of table
WriteExplainedNodesToSifFile
                        Write explained nodes to Sif file
runRankHypothesis       run rank the hypothesis
runSCANR                run ScanR
