To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("RSVSim")
In most cases, you don't need to download the package archive at all.
RSVSim
RSVSim: an R/Bioconductor package for the simulation of structural variations
Bioconductor version: 3.0
RSVSim is a package for the simulation of deletions, insertions, inversion, tandem-duplications and translocations of various sizes in any genome available as FASTA-file or BSgenome data package. SV breakpoints can be placed uniformly accross the whole genome, with a bias towards repeat regions and regions of high homology (for hg19) or at user-supplied coordinates.
Author: Christoph Bartenhagen
Maintainer: Christoph Bartenhagen <christoph.bartenhagen at uni-muenster.de>
Citation (from within R,
enter citation("RSVSim")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("RSVSim")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("RSVSim")
| R Script | RSVSim: an R/Bioconductor package for the simulation of structural variations | |
| Reference Manual |
Details
| biocViews | Sequencing, Software |
| Version | 1.6.1 |
| In Bioconductor since | BioC 2.12 (R-3.0) |
| License | LGPL-3 |
| Depends | R (>= 3.0.0), Biostrings, GenomicRanges |
| Imports | methods, IRanges, ShortRead |
| LinkingTo | |
| Suggests | BSgenome.Hsapiens.UCSC.hg19, BSgenome.Hsapiens.UCSC.hg19.masked, MASS, rtracklayer |
| 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 | RSVSim_1.6.1.tar.gz |
| Windows Binary | RSVSim_1.6.1.zip |
| Mac OS X 10.6 (Snow Leopard) | RSVSim_1.6.1.tgz |
| Mac OS X 10.9 (Mavericks) | RSVSim_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
- 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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