ternarynet

DOI: 10.18129/B9.bioc.ternarynet    

This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see ternarynet.

Ternary Network Estimation

Bioconductor version: 3.15

Gene-regulatory network (GRN) modeling seeks to infer dependencies between genes and thereby provide insight into the regulatory relationships that exist within a cell. This package provides a computational Bayesian approach to GRN estimation from perturbation experiments using a ternary network model, in which gene expression is discretized into one of 3 states: up, unchanged, or down). The ternarynet package includes a parallel implementation of the replica exchange Monte Carlo algorithm for fitting network models, using MPI.

Author: Matthew N. McCall <mccallm at gmail.com>, Anthony Almudevar <Anthony_Alumudevar at urmc.rochester.edu>, David Burton <David_Burton at urmc.rochester.edu>, Harry Stern <harry.stern at rochester.edu>

Maintainer: McCall N. Matthew <mccallm at gmail.com>

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

Installation

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

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

BiocManager::install("ternarynet")

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("ternarynet")

 

PDF R Script ternarynet: A Computational Bayesian Approach to Ternary Network Estimation
PDF   Reference Manual
Text   NEWS

Details

biocViews Bayesian, CellBiology, GraphAndNetwork, Network, Software
Version 1.40.0
In Bioconductor since BioC 2.10 (R-2.15) (10.5 years)
License GPL (>= 2)
Depends R (>= 4.0)
Imports utils, igraph, methods, graphics, stats, BiocParallel
LinkingTo
Suggests testthat
SystemRequirements
Enhances Rmpi, snow
URL
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 ternarynet_1.40.0.tar.gz
Windows Binary ternarynet_1.40.0.zip
macOS Binary (x86_64) ternarynet_1.40.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/ternarynet
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/ternarynet
Package Short Url https://bioconductor.org/packages/ternarynet/
Package Downloads Report Download Stats

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