Bioconductor version: Release (3.15)
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>
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HTML | R Script | CONDOR |
Reference Manual |
biocViews | GeneExpression, GeneRegulation, GraphAndNetwork, Microarray, Network, NetworkInference, Software, Transcription |
Version | 1.0.0 |
In Bioconductor since | BioC 3.15 (R-4.2) (0.5 years) |
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 |
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Suggests | testthat (>= 2.1.0), knitr, rmarkdown, pkgdown |
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URL | |
BugReports | https://github.com/netZoo/netZooR/issues |
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Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | netZooR_1.0.0.tar.gz |
Windows Binary | netZooR_1.0.0.zip (64-bit only) |
macOS Binary (x86_64) | netZooR_1.0.0.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/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.15 | Source Archive |
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