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biocLite("networkBMA")
In most cases, you don't need to download the package archive at all.
networkBMA
Regression-based network inference using Bayesian Model Averaging
Bioconductor version: 3.0
An extension of Bayesian Model Averaging (BMA) for network construction using time series gene expression data. Includes assessment functions and sample test data.
Author: Chris Fraley, Wm. Chad Young, Ka Yee Yeung, Adrian Raftery (with contributions from Kenneth Lo)
Maintainer: Ka Yee Yeung <kayee at u.washington.edu>
Citation (from within R,
enter citation("networkBMA")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("networkBMA")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("networkBMA")
| R Script | networkBMA | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Bayesian, GeneExpression, GeneTarget, GraphsAndNetwork, Network, NetworkInference, Software |
| Version | 1.8.0 |
| In Bioconductor since | BioC 2.11 (R-2.15) |
| License | GPL (>= 2) |
| Depends | R (>= 2.15.0), stats, utils, BMA, Rcpp (>= 0.10.3), RcppArmadillo (>= 0.3.810.2), RcppEigen (>= 0.3.1.2.1) |
| Imports | |
| LinkingTo | Rcpp, RcppArmadillo, RcppEigen |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | DREAM4 |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | networkBMA_1.8.0.tar.gz |
| Windows Binary | networkBMA_1.8.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | networkBMA_1.8.0.tgz |
| Mac OS X 10.9 (Mavericks) | networkBMA_1.8.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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