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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("CoverageView")
In most cases, you don't need to download the package archive at all.
CoverageView
Coverage visualization package for R
Bioconductor version: 3.0
This package provides a framework for the visualization of genome coverage profiles. It can be used for ChIP-seq experiments, but it can be also used for genome-wide nucleosome positioning experiments or other experiment types where it is important to have a framework in order to inspect how the coverage distributed across the genome
Author: Ernesto Lowy
Maintainer: Ernesto Lowy <ernestolowy at gmail.com>
Citation (from within R,
enter citation("CoverageView")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("CoverageView")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("CoverageView")
| R Script | Easy visualization of the read coverage | |
| Reference Manual |
Details
| biocViews | ChIPSeq, RNASeq, Sequencing, Software, Technology, Visualization |
| Version | 1.2.0 |
| In Bioconductor since | BioC 2.14 (R-3.1) |
| License | Artistic-2.0 |
| Depends | R (>= 2.10), methods, Rsamtools, rtracklayer |
| Imports | S4Vectors, IRanges, GenomicRanges, GenomicAlignments, parallel, tools |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | CoverageView_1.2.0.tar.gz |
| Windows Binary | |
| Mac OS X 10.6 (Snow Leopard) | CoverageView_1.2.0.tgz |
| Mac OS X 10.9 (Mavericks) | CoverageView_1.2.0.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
- 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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