Merge pull request #232 from marouenbg/add-bioc

add bioc information

DESCRIPTION

@@ -1,11 +1,11 @@
 Package: netZooR
-Title: Integrate methods: PANDA, LIONESS, CONDOR, ALPACA, SAMBAR, MONSTER, OTTER, EGRET, and YARN into one workflow
+Title: netZooR integrates tools for the inference and analysis of gene regulatory networks.
 Version: 0.99.85
 Date: 2021-09-20
-Authors@R: c(person("Tian", "Wang",
+Authors@R: c(person("Marouen", "Ben Guebila",
+			email = "benguebila@hsph.harvard.edu", role = c("aut","cre")),
+	     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",
@@ -16,7 +16,7 @@ Authors@R: c(person("Tian", "Wang",
 			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. 
+Description: PANDA (Passing Attributes between Networks for Data Assimilation) is a message-passing algorithm to reconstruct 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,

README.md

@@ -79,6 +79,18 @@ remotes::install_github("netZoo/netZooR", build_vignettes = TRUE)
 library(netZooR)
 ```
 
+netZooR is also available through Biocondcutor
+
+```r
+if (!requireNamespace("BiocManager", quietly = TRUE))
+    install.packages("BiocManager")
+
+# The following initializes usage of Bioc devel
+BiocManager::install(version='devel')
+
+BiocManager::install("netZooR")
+```
+
 For more details please refer to the [documentation website](https://netzoo.github.io/netZooR/).
 
 This package will invoke Python programming language in R environment through [reticulate](https://rstudio.github.io/reticulate/) package, by default setting there is no additional configuration needed.