PANR

DOI: 10.18129/B9.bioc.PANR    

This package is for version 3.11 of Bioconductor; for the stable, up-to-date release version, see PANR.

Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations

Bioconductor version: 3.11

This package provides S4 classes and methods for inferring functional gene networks with edges encoding posterior beliefs of gene association types and nodes encoding perturbation effects.

Author: Xin Wang <xin_wang at hms.harvard.edu>

Maintainer: Xin Wang <xin_wang at hms.harvard.edu>

Installation

To install this package, start R (version "4.0") and enter:

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

BiocManager::install("PANR")

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("PANR")

 

PDF	R Script	Main vignette:Posterior association network and enriched functional gene modules inferred from rich phenotypes of gene perturbations
PDF		Reference Manual
Text		NEWS

Details

biocViews	CellBasedAssays, Clustering, GraphAndNetwork, ImmunoOncology, NetworkInference, Software, Visualization
Version	1.34.0
In Bioconductor since	BioC 2.9 (R-2.14) (9 years)
License	Artistic-2.0
Depends	R (>= 2.14), igraph
Imports	graphics, grDevices, MASS, methods, pvclust, stats, utils, RedeR
LinkingTo
Suggests	snow
SystemRequirements
Enhances
URL
Depends On Me
Imports Me	Mulder2012
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	PANR_1.34.0.tar.gz
Windows Binary	PANR_1.34.0.zip
macOS 10.13 (High Sierra)	PANR_1.34.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/PANR
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/PANR
Package Short Url	https://bioconductor.org/packages/PANR/
Package Downloads Report	Download Stats