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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("netbiov")
In most cases, you don't need to download the package archive at all.
netbiov
A package for visualizing complex biological network
Bioconductor version: 3.0
A package that provides an effective visualization of large biological networks
Author: Shailesh tripathi and Frank Emmert-Streib
Maintainer: Shailesh tripathi <shailesh.tripathy at gmail.com>
Citation (from within R,
enter citation("netbiov")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("netbiov")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("netbiov")
| R Script | netbiov: An R package for visualizing biological networks | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | GraphAndNetwork, Network, Software, Visualization |
| Version | 1.0.0 |
| In Bioconductor since | BioC 3.0 (R-3.1) |
| License | GPL (>= 2) |
| Depends | R (>= 3.1.0), igraph (>= 0.7.1) |
| Imports | |
| LinkingTo | |
| Suggests | BiocStyle, RUnit, BiocGenerics, Matrix |
| SystemRequirements | |
| Enhances | |
| URL | http://www.bio-complexity.com |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | netbiov_1.0.0.tar.gz |
| Windows Binary | netbiov_1.0.0.zip |
| Mac OS X 10.6 (Snow Leopard) | netbiov_1.0.0.tgz |
| Mac OS X 10.9 (Mavericks) | netbiov_1.0.0.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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