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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("GenoView")
In most cases, you don't need to download the package archive at all.
GenoView
Condensed, overlapped plotting of genomic data tracks
Bioconductor version: 3.0
Superimposing input data over existing genomic references allows for fast, accurate visual comparisons. The GenoView package is a novel bioinformatics package which condenses genomic data tracks to offer a comprehensive view of genetic variants. Its main function is to display mutation data over exons and protein domains, which easily identifies potential genomic locations of interest.
Author: Sharon Lee, Dennis Wang
Maintainer: Sharon Lee <s274lee at uwaterloo.ca>
Citation (from within R,
enter citation("GenoView")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("GenoView")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("GenoView")
| R Script | GenoView | |
| Reference Manual |
Details
| biocViews | Software, Visualization |
| Version | 1.0.0 |
| In Bioconductor since | BioC 3.0 (R-3.1) |
| License | GPL-3 |
| Depends | R (>= 2.10), gridExtra, GenomicRanges |
| Imports | ggbio, ggplot2, grid, biovizBase |
| LinkingTo | |
| Suggests | TxDb.Hsapiens.UCSC.hg19.knownGene, PFAM.db, AnnotationDbi, gtable, gWidgets, gWidgetsRGtk2, RGtk2, RColorBrewer |
| 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 | GenoView_1.0.0.tar.gz |
| Windows Binary | GenoView_1.0.0.zip |
| Mac OS X 10.6 (Snow Leopard) | GenoView_1.0.0.tgz |
| Mac OS X 10.9 (Mavericks) | GenoView_1.0.0.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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