To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("minet")
In most cases, you don't need to download the package archive at all.
minet
Mutual Information NETworks
Bioconductor version: 3.0
This package implements various algorithms for inferring mutual information networks from data.
Author: Patrick E. Meyer, Frederic Lafitte, Gianluca Bontempi
Maintainer: Patrick E. Meyer <software at meyerp.com>
Citation (from within R,
enter citation("minet")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("minet")
Documentation
| Reference Manual | ||
| Text | LICENSE |
Details
| biocViews | GraphAndNetwork, Microarray, Network, NetworkInference, Software |
| Version | 3.24.0 |
| In Bioconductor since | BioC 2.3 (R-2.8) |
| License | file LICENSE |
| Depends | |
| Imports | infotheo |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | http://minet.meyerp.com |
| Depends On Me | BUS, geNetClassifier, netresponse |
| Imports Me | RTN |
| Suggests Me | CNORfeeder, predictionet |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | minet_3.24.0.tar.gz |
| Windows Binary | minet_3.24.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | minet_3.24.0.tgz |
| Mac OS X 10.9 (Mavericks) | minet_3.24.0.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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