To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("VegaMC")
In most cases, you don't need to download the package archive at all.
VegaMC
VegaMC: A Package Implementing a Variational Piecewise Smooth Model for Identification of Driver Chromosomal Imbalances in Cancer
Bioconductor version: 2.14
This package enables the detection of driver chromosomal imbalances including loss of heterozygosity (LOH) from array comparative genomic hybridization (aCGH) data. VegaMC performs a joint segmentation of a dataset and uses a statistical framework to distinguish between driver and passenger mutation. VegaMC has been implemented so that it can be immediately integrated with the output produced by PennCNV tool. In addition, VegaMC produces in output two web pages that allows a rapid navigation between both the detected regions and the altered genes. In the web page that summarizes the altered genes, the link to the respective Ensembl gene web page is reported.
Author: S. Morganella and M. Ceccarelli
Maintainer: Sandro Morganella <sandro at ebi.ac.uk>
Citation (from within R,
enter citation("VegaMC")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("VegaMC")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("VegaMC")
| R Script | VegaMC | |
| Reference Manual |
Details
| biocViews | CopyNumberVariation, Software, aCGH |
| Version | 3.2.0 |
| In Bioconductor since | BioC 2.10 (R-2.15) |
| License | GPL-2 |
| Depends | R (>= 2.10.0), biomaRt, Biobase, genoset |
| Imports | methods |
| Suggests | |
| 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 | VegaMC_3.2.0.tar.gz |
| Windows Binary | VegaMC_3.2.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | VegaMC_3.2.0.tgz |
| Mac OS X 10.9 (Mavericks) | VegaMC_3.2.0.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
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