Function reference • netZooR

Main functions

main functions to run each algorithm

pandaPy(): Run Python implementation PANDA in R

createCondorObject(): Create list amenable to analysis using condor package.

lioness(): Compute LIONESS (Linear Interpolation to Obtain Network Estimates for Single Samples)

alpaca(): Main ALPACA function

sambar(): Main SAMBAR function.

monster(): MOdeling Network State Transitions from Expression and Regulatory data (MONSTER)

otter(): Run OTTER in R

cobra(): Run COBRA in R

puma(): PANDA using microRNA associations

spider(): Seeding PANDA Interactions to Derive Epigenetic Regulation

tiger(): TIGER main function

runEgret(): Run EGRET in R

dragon(): Run DRAGON in R.

craneBipartite(): Pertrubs the bipartite network with fixed node strength

PANDA

All functions of PANDA

pandaPy(): Run Python implementation PANDA in R

pandaToCondorObject(): Turn PANDA network into a CONDOR object

pandaToAlpaca(): Use two PANDA network to generate an ALPACA result

pandaDiffEdges(): Identify differential edges in two PANDA networks

visPandaInCytoscape(): Plot PANDA network in Cytoscape

createPandaStyle(): Create a Cytoscape visual style for PANDA network

CONDOR

All functions of CONDOR

createCondorObject(): Create list amenable to analysis using condor package.

condorCluster(): Main clustering function for condor.

condorCoreEnrich(): Compare qscore distribution of a subset of nodes to all other nodes.

condorCreateObject(): creates condor object

condorMatrixModularity(): Iteratively maximize bipartite modularity.

condorModularityMax(): Iteratively maximize bipartite modularity.

condorPlotCommunities(): Plot adjacency matrix with links grouped and colored by community

condorPlotHeatmap(): Plot weighted adjacency matrix with links grouped by community

condorQscore(): Calculate Qscore for all nodes

condorRun(): Run CONDOR clustering

LIONESS

All functions of LIONESS

lionessPy(): Run python implementation of LIONESS

lioness(): Compute LIONESS (Linear Interpolation to Obtain Network Estimates for Single Samples)

ALPACA

All functions of ALPACA

alpaca(): Main ALPACA function

alpacaCommunityStructureRotation(): Comparing node community membership between two networks

alpacaComputeDWBMmatmScale(): Differential modularity matrix

alpacaComputeDifferentialScoreFromDWBM(): Compute Differential modularity score from differential modularity matrix

alpacaComputeWBMmat(): Compute modularity matrix for weighted bipartite network

alpacaCrane(): Find the robust nodes in ALPACA community using CRANE

alpacaDeltaZAnalysis(): Edge subtraction method (CONDOR optimizaton)

alpacaDeltaZAnalysisLouvain(): Edge subtraction method (Louvain optimizaton)

alpacaExtractTopGenes(): Extract core target genes in differential modules

alpacaGOtabtogenes(): The top GO term associated genes in each module

alpacaGenLouvain(): Generalized Louvain optimization

alpacaGetMember(): get the member vector from alpaca object

alpacaGoToGenes(): Map GO terms to gene symbols

alpacaListToGo(): GO term enrichment for a list of gene sets

alpacaMetaNetwork(): Create alpacaMetaNetwork for Louvain optimization

alpacaNodeToGene(): Remove tags from gene names

alpacaObjectToDfList(): Converts alpaca output into list of data frames

alpacaRotationAnalysis(): Community comparison method (CONDOR optimizaton)

alpacaRotationAnalysisLouvain(): Community comparison method (CONDOR optimizaton)

alpacaSimulateNetwork(): Simulated networks

alpacaTestNodeRank(): Enrichment in ranked list

alpacaTidyConfig(): Renumbering community membership vector

alpacaTopEnsembltoTopSym(): Translating gene identifiers to gene symbols

alpacaWBMlouvain(): Generalized Louvain method for bipartite networks

SAMBAR

All functions of SAMBAR

sambar(): Main SAMBAR function.

sambarConvertgmt(): Convert .gmt files into a binary matrix.

sambarCorgenelength(): Normalize gene mutation scores by gene length.

sambarDesparsify(): De-sparsify gene-level mutation scores into gene set-level mutation scores.

MONSTER

All functions of MONSTER

monster(): MOdeling Network State Transitions from Expression and Regulatory data (MONSTER)

monsterBereFull(): Bipartite Edge Reconstruction from Expression data (composite method with direct/indirect)

monsterCalculateTmPValues(): Calculate p-values for a tranformation matrix

monsterCheckDataType(): Checks that data is something MONSTER can handle

monsterGetTm(): monsterGetTm

monsterHclHeatmapPlot(): Transformation matrix plot

monsterMonsterNI(): Bipartite Edge Reconstruction from Expression data

monsterPlotMonsterAnalysis(): monsterPlotMonsterAnalysis

monsterPrintMonsterAnalysis(): monsterPrintMonsterAnalysis

monsterRes: MONSTER results from example cell-cycle yeast transition

monsterTransformationMatrix(): Bi-partite network analysis tools

monsterTransitionNetworkPlot(): This function uses igraph to plot the transition matrix (directed graph) as a network. The edges in the network should be read as A 'positively/negatively contributes to' the targeting of B in the target state.

monsterTransitionPCAPlot(): Principal Components plot of transformation matrix

monsterdTFIPlot(): This function plots the Off diagonal mass of an observed Transition Matrix compared to a set of null TMs

OTTER

OTTER functions

otter(): Run OTTER in R

TIGER

TIGER functions

tiger(): TIGER main function

TIGER_expr: TIGER example expression matrix

TIGER_prior: TIGER example prior network

adj2regulon(): Convert bipartite adjacency to regulon

priorPp(): Filter low confident edge signs in the prior network using GeneNet

COBRA

COBRA functions

cobra(): Run COBRA in R

CRANE

CRANE functions

craneBipartite(): Pertrubs the bipartite network with fixed node strength

craneUnipartite(): Pertrubs the unipartite network with fixed node strength from adjacency matrix

elistToAdjMat(): Converts edge list to adjacency matrix

elistSort(): Sorts the edge list based on first two columns in alphabetical order

elistRemoveTags(): undo elistAddTags

isElist(): Check if data frame is an edge list

adjMatToElist(): converts adjacency matrix to edge list

el2adj(): Convert bipartite edge list to adjacency mat

el2regulon(): Convert a bipartite edgelist to regulon

elistIsEdgeOrderEqual(): check if first two columns are identical

elistAddTags(): Adds "_A" to first column and "_B" to second column

adj2el(): Convert a bipartite adjacency matrix to an edgelist

jutterDegree(): CRANE Beta perturbation function. This function will add noice to the node strength sequence.

DRAGON

DRAGON functions

dragon(): Run DRAGON in R.

SPIDER

SPIDER functions

spider(): Seeding PANDA Interactions to Derive Epigenetic Regulation

degreeAdjust(): Function to adjust the degree so that the hub nodes are not penalized in z-score transformation

PUMA

PUMA functions

puma(): PANDA using microRNA associations

EGRET

EGRET functions

runEgret(): Run EGRET in R

Plotting functions

function to plot the networks and community structures.

createPandaStyle(): Create a Cytoscape visual style for PANDA network

condorPlotCommunities(): Plot adjacency matrix with links grouped and colored by community

condorPlotHeatmap(): Plot weighted adjacency matrix with links grouped by community

Helper functions

miscellaneous function

sourcePPI(): Source the Protein-Protein interaction in STRING database

pandaToCondorObject(): Turn PANDA network into a CONDOR object

pandaToAlpaca(): Use two PANDA network to generate an ALPACA result

Data

Input example data files

yeast: Toy data derived from three gene expression datasets and a mapping from transcription factors to genes.

small1976: Pollinator-plant interactions

mut.ucec mut.ucec: Example of mutation data

exon.size exon.size genes: Gene length

genes: Example of a gene list