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- GeneNetworkBuilder
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("GeneNetworkBuilder")
In most cases, you don't need to download the package archive at all.
GeneNetworkBuilder
Build Regulatory Network from ChIP-chip/ChIP-seq and Expression Data
Bioconductor version: 2.14
Appliation for discovering direct or indirect targets of transcription factors using ChIP-chip or ChIP-seq, and microarray or RNA-seq gene expression data. Inputting a list of genes of potential targets of one TF from ChIP-chip or ChIP-seq, and the gene expression results, GeneNetworkBuilder generates a regulatory network of the TF.
Author: Jianhong Ou and Lihua Julie Zhu
Maintainer: Jianhong Ou <jianhong.ou at umassmed.edu>
Citation (from within R,
enter citation("GeneNetworkBuilder")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("GeneNetworkBuilder")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("GeneNetworkBuilder")
| R Script | GeneNetworkBuilder Vignette | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | GraphAndNetwork, Microarray, Sequencing, Software |
| Version | 1.6.1 |
| In Bioconductor since | BioC 2.11 (R-2.15) |
| License | GPL (>= 2) |
| Depends | R (>= 2.15.1), Rcpp (>= 0.9.13), graph |
| Imports | plyr, graph |
| Suggests | RUnit, BiocGenerics, Rgraphviz, XML, RCytoscape, RBGL |
| System Requirements | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | GeneNetworkBuilder_1.6.1.tar.gz |
| Windows Binary | GeneNetworkBuilder_1.6.1.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | GeneNetworkBuilder_1.6.1.tgz |
| Mac OS X 10.9 (Mavericks) | GeneNetworkBuilder_1.6.1.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
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