Package: netZooR 1.17.0

Marouen Ben Guebila

netZooR: A menagerie of methods for the inference and analysis of gene regulatory networks

netZooR unifies the implementations of several Network Zoo methods (netzoo, netzoo.github.io) into a single package by creating interfaces between network inference and network analysis methods. Currently, the package has 3 methods for network inference including PANDA and its optimized implementation OTTER (network reconstruction using mutliple lines of biological evidence), LIONESS (single-sample network inference), and EGRET (genotype-specific networks). Network analysis methods include CONDOR (community detection), ALPACA (differential community detection), CRANE (significance estimation of differential modules), MONSTER (estimation of network transition states). In addition, YARN allows to process gene expresssion data for tissue-specific analyses and SAMBAR infers missing mutation data based on pathway information.

Authors:Tara Eicher [aut], Marouen Ben Guebila [aut, cre], Tian Wang [aut], John Platig [aut], Marieke Kuijjer [aut], Megha Padi [aut], Rebekka Burkholz [aut], Des Weighill [aut], Chen Chen [aut], Kate Shutta [aut]

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
netZooR/json (API)

# Install 'netZooR' in R:

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

Bug tracker:https://github.com/netzoo/netzoor/issues

Datasets:

bladder - Bladder RNA-seq data from the GTEx consortium
exon.size - Gene length
genes - Example of a gene list
monsterRes - MONSTER results from example cell-cycle yeast transition
mut.ucec - Example of mutation data
skin - Skin RNA-seq data from the GTEx consortium
small1976 - Pollinator-plant interactions
TIGER_expr - TIGER example expression matrix
TIGER_prior - TIGER example prior network
yeast - Toy data derived from three gene expression datasets and a mapping from transcription factors to genes.

On BioConductor:netZooR-1.17.0(bioc 3.24)netZooR-1.16.0(bioc 3.23)

geneexpression generegulation graphandnetwork microarray network networkinference transcription gene-regulatory-network transcription-factors

8.72 score 120 stars 145 scripts 198 downloads 70 exports 218 dependencies

Last updated from:ad27b19fcd. Checks:8 ERROR, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	257
linux-devel	ERROR	639
source / vignettes	OK	638
linux-release	ERROR	737
macos-release	ERROR	626
macos-oldrel	ERROR	509
windows-devel	ERROR	519
windows-release	ERROR	624
windows-oldrel	ERROR	705
wasm-release	OK	273

Exports:adj2el adj2regulon alpaca alpacaCrane alpacaExtractTopGenes alpacaListToGo annotateFromBiomart CalculatePValues checkMisAnnotation checkTissuesToMerge cobra condorCluster condorCoreEnrich condorMatrixModularity condorModularityMax condorPlotCommunities condorPlotHeatmap condorQscore craneBipartite craneUnipartite createCondorObject createPandaStyle domonster downloadGTEx dragon el2adj el2regulon elistToAdjMat filterGenes filterLowGenes filterMissingGenes filterSamples GenerateNullPANDADistribution lioness lionessPy monster monsterBereFull monsterCalculateTmPValues monsterCalculateTmStats monsterCheckDataType monsterdTFIPlot monsterGetTm monsterHclHeatmapPlot monsterMonsterNI monsterPlotMonsterAnalysis monsterPrintMonsterAnalysis monsterTransformationMatrix monsterTransitionNetworkPlot monsterTransitionPCAPlot normalizeTissueAware otter pandaDiffEdges pandaPy pandaToAlpaca pandaToCondorObject plotCMDS plotDensity plotHeatmap PlotNetwork priorPp puma RunBLOBFISH runEgret sambar sambarConvertgmt sambarCorgenelength sourcePPI spider tiger visPandaInCytoscape

Dependencies:abind annotate AnnotationDbi AnnotationForge askpass assertthat backports base64 base64enc base64url beanplot BH Biobase BiocBaseUtils BiocFileCache BiocGenerics BiocIO biocmake BiocParallel biomaRt Biostrings bit bit64 bitops blob bumphunter cachem Category caTools checkmate chron cigarillo cli clipr cluster cmdstanr codetools corpcor cpp11 crayon curl data.table DBI dbplyr DelayedArray DelayedMatrixStats digest dir.expiry distributional doParallel doRNG downloader dplyr edgeR evaluate farver fastmap fdrtool filelock foreach formatR fs futile.logger futile.options genefilter GeneNet generics GenomicAlignments GenomicFeatures GenomicRanges GEOquery ggdendro ggplot2 glue GO.db GOstats gplots graph GSEABase gsubfn gtable gtools h5mread hash HDF5Array here hexbin hms htmltools httr httr2 igraph illuminaio IRanges IRdisplay IRkernel isoband iterators jsonlite KEGGREST KernSmooth labeling lambda.r lattice lifecycle limma locfit longitudinal loo magrittr MASS Matrix matrixcalc MatrixGenerics matrixStats matrixTests mclust memoise mgcv mime minfi multtest nlme nnet nor1mix numDeriv openssl org.Hs.eg.db pandaR pbdZMQ penalized permute pillar pkgconfig plotrix plyr png posterior preprocessCore prettyunits progress proto purrr quadprog quantro R.methodsS3 R.oo R.utils R6 rappdirs rARPACK RBGL RColorBrewer Rcpp RcppArmadillo RcppEigen RcppTOML RCurl RCy3 readr rentrez repr reshape reshape2 restfulr reticulate Rgraphviz rhdf5 rhdf5filters Rhdf5lib Rhtslib rjson RJSONIO rlang rngtools rprojroot Rsamtools RSpectra RSQLite rtracklayer RUnit rvest S4Arrays S4Vectors S7 scales scrime selectr Seqinfo siggenes snow SparseArray sparseMatrixStats sqldf statmod STRINGdb stringi stringr SummarizedExperiment survival sys tensorA tibble tidyr tidyselect tzdb utf8 uuid vctrs vegan viridisLite vroom withr XML xml2 xtable XVector yaml

Using CONDOR for community detection in bipartite graphs

Introduction | Installation | Implementing the Bipartite Modularity Maximization | Workflow | Session Information

Rendered fromCONDOR.Rmdusingknitr::rmarkdown

Last update: 2021-11-14
Started: 2020-12-06

Help page	Topics
Convert a bipartite adjacency matrix to an edgelist	adj2el
Convert bipartite adjacency to regulon	adj2regulon
converts adjacency matrix to edge list	adjMatToElist
Main ALPACA function	alpaca
Comparing node community membership between two networks	alpacaCommunityStructureRotation
Compute Differential modularity score from differential modularity matrix	alpacaComputeDifferentialScoreFromDWBM
Differential modularity matrix	alpacaComputeDWBMmatmScale
Compute modularity matrix for weighted bipartite network	alpacaComputeWBMmat
Find the robust nodes in ALPACA community using CRANE	alpacaCrane
Edge subtraction method (CONDOR optimizaton)	alpacaDeltaZAnalysis
Edge subtraction method (Louvain optimizaton)	alpacaDeltaZAnalysisLouvain
Extract core target genes in differential modules	alpacaExtractTopGenes
Generalized Louvain optimization	alpacaGenLouvain
get the member vector from alpaca object	alpacaGetMember
The top GO term associated genes in each module	alpacaGOtabtogenes
Map GO terms to gene symbols	alpacaGoToGenes
GO term enrichment for a list of gene sets	alpacaListToGo
Create alpacaMetaNetwork for Louvain optimization	alpacaMetaNetwork
Remove tags from gene names	alpacaNodeToGene
Converts alpaca output into list of data frames	alpacaObjectToDfList
Community comparison method (CONDOR optimizaton)	alpacaRotationAnalysis
Community comparison method (CONDOR optimizaton)	alpacaRotationAnalysisLouvain
Simulated networks	alpacaSimulateNetwork
Enrichment in ranked list	alpacaTestNodeRank
Renumbering community membership vector	alpacaTidyConfig
Translating gene identifiers to gene symbols	alpacaTopEnsembltoTopSym
Generalized Louvain method for bipartite networks	alpacaWBMlouvain
Annotate your Expression Set with biomaRt	annotateFromBiomart
Bladder RNA-seq data from the GTEx consortium	bladder
Find the subnetwork of significant edges connecting the genes.	BuildSubnetwork
Calculate p-values for all edges in the network using a Wilcoxon two-sample test for each edge.	CalculatePValues
Check for wrong annotation of a sample using classical MDS and control genes.	checkMisAnnotation
Check tissues to merge based on gene expression profile	checkTissuesToMerge
Run COBRA in R	cobra
Main clustering function for condor.	condorCluster
Compare qscore distribution of a subset of nodes to all other nodes.	condorCoreEnrich
creates condor object	condorCreateObject
Iteratively maximize bipartite modularity.	condorMatrixModularity
Iteratively maximize bipartite modularity.	condorModularityMax
Plot adjacency matrix with links grouped and colored by community	condorPlotCommunities
Plot weighted adjacency matrix with links grouped by community	condorPlotHeatmap
Calculate Qscore for all nodes	condorQscore
Run CONDOR clustering	condorRun
Pertrubs the bipartite network with fixed node strength	craneBipartite
Pertrubs the unipartite network with fixed node strength from adjacency matrix	craneUnipartite
Create list amenable to analysis using 'condor' package.	createCondorObject
Create a Cytoscape visual style for PANDA network	createPandaStyle
Function to adjust the degree so that the hub nodes are not penalized in z-score transformation	degreeAdjust
MONSTER quick-start with pre-made regulatory networks	domonster
Download GTEx files and turn them into ExpressionSet object	downloadGTEx
Run DRAGON in R.	dragon
Convert bipartite edge list to adjacency mat	el2adj
Convert a bipartite edgelist to regulon	el2regulon
Adds "_A" to first column and "_B" to second column	elistAddTags
check if first two columns are identical	elistIsEdgeOrderEqual
undo elistAddTags	elistRemoveTags
Sorts the edge list based on first two columns in alphabetical order	elistSort
Converts edge list to adjacency matrix	elistToAdjMat
Gene length	exon.size
Extract the appropriate matrix	extractMatrix
Filter specific genes	filterGenes
Filter genes that have less than a minimum threshold CPM for a given group/tissue	filterLowGenes
Filter genes not expressed in any sample	filterMissingGenes
Filter samples	filterSamples
For all hop counts up to the maximum, find subnetworks connecting each pair of genes by exactly that number of hops. For instance, find each	FindConnectionsForAllHopCounts
Find the subnetwork of significant edges n / 2 hops away from each gene.	FindSignificantEdgesForHop
Generate a null distribution of edge scores for PANDA-like networks; that is, the set of edges where (1) the TF does not have a binding motif in the gene region, (2) the TF does not form a complex with any other TF that has a binding motif in the gene region, and (3) the genes regulated by the TF are not coexpressed with the gene in question. We obtain this by inputting an empty prior and an identity coexpression matrix.	GenerateNullPANDADistribution
Example of a gene list	genes
Check if data frame is an edge list	isElist
CRANE Beta perturbation function. This function will add noice to the node strength sequence.	jutterDegree
Compute LIONESS (Linear Interpolation to Obtain Network Estimates for Single Samples)	lioness
Run python implementation of LIONESS	lionessPy
MOdeling Network State Transitions from Expression and Regulatory data (MONSTER)	monster
Bipartite Edge Reconstruction from Expression data (composite method with direct/indirect)	monsterBereFull
Calculate p-values for a tranformation matrix	monsterCalculateTmPValues
Calculate statistics for a tranformation matrix	monsterCalculateTmStats
Checks that data is something MONSTER can handle	monsterCheckDataType
This function plots the Off diagonal mass of an observed Transition Matrix compared to a set of null TMs	monsterdTFIPlot
monsterGetTm	monsterGetTm
Transformation matrix plot	monsterHclHeatmapPlot
Bipartite Edge Reconstruction from Expression data	monsterMonsterNI
monsterPlotMonsterAnalysis	monsterPlotMonsterAnalysis
monsterPrintMonsterAnalysis	monsterPrintMonsterAnalysis
MONSTER results from example cell-cycle yeast transition	monsterRes
Bi-partite network analysis tools	monsterTransformationMatrix
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.	monsterTransitionNetworkPlot
Principal Components plot of transformation matrix	monsterTransitionPCAPlot
Example of mutation data	mut.ucec
Normalize in a tissue aware context	normalizeTissueAware
Run OTTER in R	otter
Identify differential edges in two PANDA networks	pandaDiffEdges
Run Python implementation PANDA in R	pandaPy
Use two PANDA network to generate an ALPACA result	pandaToAlpaca
Turn PANDA network into a CONDOR object	pandaToCondorObject
Plot classical MDS of dataset	plotCMDS
Density plots of columns in a matrix	plotDensity
Plot heatmap of most variable genes	plotHeatmap
Plot the networks, using different colors for transcription factors, genes of interest, and additional genes.	PlotNetwork
Filter low confident edge signs in the prior network using GeneNet	priorPp
PANDA using microRNA associations	puma
Quantile shrinkage normalization	qsmooth
Compute quantile statistics	qstats
Given a set of genes of interest, full bipartite networks with scores (one network for each sample), a significance cutoff for statistical testing, and a hop constraint, BLOBFISH finds a subnetwork of significant edges connecting the genes.	RunBLOBFISH
Run EGRET in R	runEgret
Main SAMBAR function.	sambar
Convert .gmt files into a binary matrix.	sambarConvertgmt
Normalize gene mutation scores by gene length.	sambarCorgenelength
De-sparsify gene-level mutation scores into gene set-level mutation scores.	sambarDesparsify
Find all significant edges adjacent to the starting nodes, excluding the nodes specified.	SignificantBreadthFirstSearch
Skin RNA-seq data from the GTEx consortium	skin
Pollinator-plant interactions	small1976
Source the Protein-Protein interaction in STRING database	sourcePPI
Seeding PANDA Interactions to Derive Epigenetic Regulation	spider
TIGER main function	tiger
TIGER example expression matrix	TIGER_expr
TIGER example prior network	TIGER_prior
Plot PANDA network in Cytoscape	visPandaInCytoscape
Toy data derived from three gene expression datasets and a mapping from transcription factors to genes.	yeast

Package: netZooR 1.17.0

netZooR: A menagerie of methods for the inference and analysis of gene regulatory networks

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