netZooR

DOI: 10.18129/B9.bioc.netZooR    

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

Integrate methods: PANDA, LIONESS, CONDOR, ALPACA, SAMBAR, MONSTER, OTTER, EGRET, and YARN into one workflow

Bioconductor version: Development (3.16)

PANDA(Passing Attributes between Networks for Data Assimilation) is a message-passing model to reconstruction gene regulatory network. It integrates multiple sources of biological data, including protein-protein interaction data, gene expression data, and sequence motif information to reconstruct genome-wide, condition-specific regulatory networks.[(Glass et al. 2013)]. LIONESS(Linear Interpolation to Obtain Network Estimates for Single Samples) is a method to estimate sample-specific regulatory networks by applying linear interpolation to the predictions made by existing aggregate network inference approaches. CONDOR(COmplex Network Description Of Regulators)is a bipartite community structure analysis tool of biological networks, especially eQTL networks, including a method for scoring nodes based on their modularity contribution.[(Platig et al. 2016). ALPACA(ALtered Partitions Across Community Architectures) is a method for comparing two genome-scale networks derived from different phenotypic states to identify condition-specific modules.[(Padi and Quackenbush 2018)]. This package integrates pypanda--the Python implementation of PANDA and LIONESS(https://github.com/davidvi/pypanda),the R implementation of CONDOR(https://github.com/jplatig/condor) and the R implementation of ALPACA (https://github.com/meghapadi/ALPACA) into one workflow. Each tool can be call in this package by one function, and the relevant output could be accessible in current R session for downstream analysis.

Author: Tian Wang [aut], Marouen Ben Guebila [aut, cre], John Platig [aut], Marieke Kuijjer [aut], Magha Padi [aut], Rebekka Burkholz [aut], Deborah Weighill [aut]

Maintainer: Marouen Ben Guebila <marouen.b.guebila at gmail.com>

Citation (from within R, enter citation("netZooR")):

Installation

To install this package, start R (version "4.2") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("netZooR")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("netZooR")

 

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Details

biocViews GeneExpression, GeneRegulation, GraphAndNetwork, Microarray, Network, NetworkInference, Software, Transcription
Version 1.1.0
In Bioconductor since BioC 3.15 (R-4.2) (< 6 months)
License GPL-3
Depends R (>= 4.1.0), igraph, reticulate, pandaR, yarn
Imports RCy3, viridisLite, STRINGdb, Biobase, GOstats, AnnotationDbi, matrixStats, GO.db, org.Hs.eg.db, Matrix, gplots, nnet, data.table, vegan, stats, utils, reshape, reshape2, penalized, parallel, doParallel, foreach, ggplot2, ggdendro, grid, MASS, assertthat, tidyr, methods, dplyr, graphics
LinkingTo
Suggests testthat (>= 2.1.0), knitr, rmarkdown, pkgdown
SystemRequirements
Enhances
URL
BugReports https://github.com/netZoo/netZooR/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package netZooR_1.1.0.tar.gz
Windows Binary netZooR_1.1.0.zip
macOS 10.13 (High Sierra) netZooR_1.1.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/netZooR
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/netZooR
Package Short Url https://bioconductor.org/packages/netZooR/
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