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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("epivizr")
In most cases, you don't need to download the package archive at all.
epivizr
R Interface to epiviz web app
Bioconductor version: 2.14
This package provides Websocket communication to the epiviz web app (http://epiviz.cbcb.umd.edu) for interactive visualization of genomic data. Objects in R/bioc interactive sessions can be displayed in genome browser tracks or plots to be explored by navigation through genomic regions. Fundamental Bioconductor data structures are supported (e.g., GenomicRanges and SummarizedExperiment objects), while providing an easy mechanism to support other data structures. Visualizations (using d3.js) can be easily added to the web app as well.
Author: Hector Corrada Bravo, Florin Chelaru, Llewellyn Smith, Naomi Goldstein
Maintainer: Hector Corrada Bravo <hcorrada at gmail.com>
Citation (from within R,
enter citation("epivizr")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("epivizr")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("epivizr")
| HTML | R Script | Introduction to epivizr |
| Reference Manual |
Details
| biocViews | GUI, Infrastructure, Software, Visualization |
| Version | 1.2.12 |
| In Bioconductor since | BioC 2.13 (R-3.0) |
| License | GPL-3 |
| Depends | R (>= 3.0.1), methods, Biobase, GenomicRanges(>= 1.13.47) |
| Imports | httpuv (>= 1.3.0), rjson, IRanges |
| Suggests | testthat, roxygen2, knitr, antiProfilesData, hgu133plus2.db, knitrBootstrap |
| 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 | epivizr_1.2.12.tar.gz |
| Windows Binary | epivizr_1.2.12.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | epivizr_1.2.12.tgz |
| Mac OS X 10.9 (Mavericks) | epivizr_1.2.12.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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