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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("epigenomix")
In most cases, you don't need to download the package archive at all.
epigenomix
Epigenetic and gene transcription data normalization and integration with mixture models
Bioconductor version: 2.14
A package for the integrative analysis of RNA-seq or microarray based gene transcription and histone modification data obtained by ChIP-seq. The package provides methods for data preprocessing and matching as well as methods for fitting bayesian mixture models in order to detect genes with differences in both data types.
Author: Hans-Ulrich Klein, Martin Schaefer
Maintainer: Hans-Ulrich Klein <h.klein at uni-muenster.de>
Citation (from within R,
enter citation("epigenomix")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("epigenomix")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("epigenomix")
| R Script | epigenomix package vignette | |
| Reference Manual |
Details
| biocViews | ChIPSeq, Classification, DifferentialExpression, GeneExpression, Software |
| Version | 1.4.1 |
| In Bioconductor since | BioC 2.12 (R-3.0) |
| License | LGPL-3 |
| Depends | R (>= 2.12.0), methods, Biobase, IRanges, GenomicRanges |
| Imports | BiocGenerics, beadarray |
| 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 | epigenomix_1.4.1.tar.gz |
| Windows Binary | epigenomix_1.4.1.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | epigenomix_1.4.1.tgz |
| Mac OS X 10.9 (Mavericks) | epigenomix_1.4.1.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
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