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All functions

applySparrowBonferroni()
Applies Bonferroni Correction to a Sparrow Network Object
applySparrowFDR()
Applies FDR Correction to a Sparrow Network Object
aracne()
This function applies ARACNE on the data
arbitrarySparsity()
This function Builds an arbitary sparse network
buildConsensus()
This function builds the Consensus Network from the component network
c3netWrapper()
This function wraps c3net implementation
calcHyperPval()
Compute Hypergeometric PValue
compute(<LocalModularity>)
Find Local Modularity (NQ)
compute(<Modularity>)
Find Global Modularity (Q)
compute(<ModularityDensity>)
Find Global Modularity (Qds)
compute(<ModuleQualityMetric>)
Find Modularity Quality
computeBICcurve()
This Function Computes a Network BIC Curve
computeDriverDistance()
Compute Graph Distance
computeDriverDistancePvalue()
Compute Driver Distance P-Value
correlation()
Compute a Correlation Matrix
covarianceSelection()
Covariance Selection with Graphical Lasso
covarianceSelectionBisection()
Covariance Selection with Bisection Optimization
covarianceSelectionMBPath()
Covariance based on Neighborhood Selection
covarianceSelectionPath()
Covariance Selection with Path BIC Selection
deployNetworkSparsity()
This function deploys arbitary sparsity on a list of networks
fastlm()
Fast Linear Modeling
fastlmbic()
Fast Linear Modeling BIC
fdrThres()
FDR Threshold
findModules.CFinder()
Find Modules with CFinder
findModules.CFinder.once()
This function tries to get modules from network adjacency matrix using Link communities algorithm.
findModules.GANXiS()
Find Modules with GANXiS
findModules.GANXiS.once()
Find Modules using GANXIS
findModules.consensusCluster()
Finds Consensus Clusters
findModules.consensusKmeans()
Finds Moduless With Kmeans Clustering
findModules.edge_betweenness()
Find Modules with Network Adjacency
findModules.edge_betweenness.once()
Find Modules with Network Adjacency Single iteration
findModules.fast_greedy()
Find Modules with iGraph Fast and Greedy algorithm
findModules.fast_greedy.once()
Find Modules Fast and Greedy
findModules.hclust()
Find Modules with Hierarchical Clustering
findModules.infomap()
Find Modules using graph adjacency
findModules.infomap.once()
Find Modules using graph adjacency
findModules.label_prop()
Wraps Finding Modules with Graph Adjacency
findModules.label_prop.once()
Find Modules with Graph Adjacency
findModules.leading_eigen()
Find Modules with Leading Eigen Edges
findModules.leading_eigen.once()
Find Modules with Leading Eigen Edges
findModules.linkcommunities()
Find Modules with Network Adjacency Matrix Using Link Communities Algorithm
findModules.linkcommunities.once()
Find Modules with Network Adjacency Matrix Using Link Communities Algorithm
findModules.louvain()
Find Modules with Network Adjacency Matrix Using Louvain Clustering
findModules.louvain.once()
Find Modules with Network Adjacency Matrix Using Louvain Clustering
findModules.megena()
Find Modules with Megena Clustering
findModules.spinglass()
Find Modules with Network Adjacency Matrix Using Spinglass Clustering
findModules.spinglass.once()
Find Modules with Network Adjacency Matrix Using spinglass Clustering
findModules.walktrap()
Find Modules with Network Adjacency Matrix Using Walktrap Clustering
findModules.walktrap.once()
Find Modules with Network Adjacency Matrix Using Walktrap Clustering
fisherEnrichment()
Fishers Enrichment Analysis
genie3()
Run genie3
installAracne()
This function applies ARACNE on the data
lassoAIC()
Grab AIC Solution for Lasso
lassoBIC()
Grab BIC Solution for Lasso
lassoCV1se()
Grab CV1se Solution for Lasso Regression
lassoCVmin()
Grab CV1min Solution for Lasso Regression
metaNet-package
metaNet: Statistical network exploration toolkit
mpiWrapper()
Runs Sparrow Regression
mrnetWrapper()
Implements mrnet
multiplot()
Multiple plot function
rankConsensus()
Ranks Consensus networks
rankConsensus2()
Ranks Consensus networks with ties.
rankedEdgeList()
Rank edges of a coexpression matrix
regulatorAnalysis.directed()
Function to Identify Network Regulators from Directed Networks
regulatorAnalysis.directed_weighted()
Function to Identify Network Regulators from Directed Weighted Networks
regulatorAnalysis.undirected()
Function to Identify Network Regulators from Undirected Networks
regulatorAnalysis.undirected_weighted()
Function to Identify Network Regulators from Undirected Weighted Networks
ridgeAIC()
Grab AIC Solution for Ridge Regression
ridgeBIC()
Grab BIC Solution for Ridge Regression
ridgeCV1se()
Grab CV1se Solution for Ridge Regression
ridgeCVmin()
Grab CV1min Solution for Ridge Regression
run.consensus.cluster()
Runs Consensus Clustering Algorithm
score.nodes()
Scores Nodes From Regulator Discovery
simulateNetworkData()
Simulate Network Data
sparrow2Z()
Runs vbsr with a 2Z cutoff for a gene across a matrix
sparrowNetwork()
Runs wraps vbsr across a matrix
sparrowZ()
Runs vbsr gene across a matrix
synGetFiles()
This function pulls files from a synapse project
tigress()
Runs tigress on an expression matrix
wgcnaSoftThreshold()
Runs WGCNA
wgcnaTOM()
Runs WGCNA TOMsimilarity
winsorizeData()
Winsorize a Gene Expression Matrix