DOI: 10.18129/B9.bioc.netZooR    

This is the development version of netZooR; for the stable release version, see netZooR.

Unified methods for the inference and analysis of gene regulatory networks

Bioconductor version: Development (3.17)

netZooR unifies the implementations of several Network Zoo methods (netzoo, 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.

Author: Marouen Ben Guebila [aut, cre] , Tian Wang [aut] , John Platig [aut], Marieke Kuijjer [aut] , Megha Padi [aut] , Rebekka Burkholz [aut], Des Weighill [aut] , Kate Shutta [ctb]

Maintainer: Marouen Ben Guebila <benguebila at>

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biocViews GeneExpression, GeneRegulation, GraphAndNetwork, Microarray, Network, NetworkInference, Software, Transcription
Version 1.3.0
In Bioconductor since BioC 3.15 (R-4.2) (0.5 years)
License GPL-3
Depends R (>= 4.2.0), igraph, reticulate, pandaR, yarn
Imports RCy3, viridisLite, STRINGdb, Biobase, GOstats, AnnotationDbi, matrixStats, GO.db,, Matrix, gplots, nnet, data.table, vegan, stats, utils, reshape, reshape2, penalized, parallel, doParallel, foreach, ggplot2, ggdendro, grid, MASS, assertthat, tidyr, methods, dplyr, graphics
Suggests testthat (>= 2.1.0), knitr, rmarkdown, pkgdown
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