Package: netZooR
Title: Integrate methods: PANDA, LIONESS, CONDOR, ALPACA, SAMBAR,
        MONSTER, OTTER, EGRET, and YARN into one workflow
Version: 1.0.0
Date: 2021-09-20
Authors@R: c(person("Tian", "Wang",
			email = "tian.wang@bc.edu", role = c("aut")),
	     person("Marouen", "Ben Guebila", 
			email = "marouen.b.guebila@gmail.com", role = c("aut","cre")),
	     person("John", "Platig",
			email="john.platig@channing.harvard.edu",role="aut"),
	     person("Marieke", "Kuijjer",
			email = "marieke.kuijjer@ncmm.uio.no", role = "aut"),
	     person("Magha", "Padi",
			email = "mpadi@email.arizona.edu", role = "aut"),
	     person("Rebekka", "Burkholz",
			email = "rburkholz@hsph.harvard.edu",role = "aut"),
             person("Deborah", "Weighill",
                        email = "",role = "aut"))
Description: 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. 
Depends: R (>= 4.1.0), igraph, reticulate, pandaR, yarn
biocViews: NetworkInference, Network, GeneRegulation, GeneExpression,
        Transcription, Microarray, GraphAndNetwork
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
License: GPL-3
Encoding: UTF-8
LazyData: false
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, pkgdown
VignetteEngine: knitr
VignetteBuilder: knitr
RoxygenNote: 7.1.2
BugReports: https://github.com/netZoo/netZooR/issues
git_url: https://git.bioconductor.org/packages/netZooR
git_branch: RELEASE_3_15
git_last_commit: 9f0e4a2
git_last_commit_date: 2022-04-26
Date/Publication: 2022-04-27
NeedsCompilation: no
Packaged: 2022-04-28 01:19:21 UTC; biocbuild
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@gmail.com>
Built: R 4.2.0; ; 2022-04-28 11:06:16 UTC; windows
