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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("AffyCompatible")
In most cases, you don't need to download the package archive at all.
AffyCompatible
Affymetrix GeneChip software compatibility
Bioconductor version: 3.0
This package provides an interface to Affymetrix chip annotation and sample attribute files. The package allows an easy way for users to download and manage local data bases of Affynmetrix NetAffx annotation files. The package also provides access to GeneChip Operating System (GCOS) and GeneChip Command Console (AGCC)-compatible sample annotation files.
Author: Martin Morgan, Robert Gentleman
Maintainer: Martin Morgan <mtmorgan at fhcrc.org>
Citation (from within R,
enter citation("AffyCompatible")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("AffyCompatible")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("AffyCompatible")
| R Script | Annotation retrieval with NetAffxResource | |
| R Script | Retrieving MAGE and ARR sample attributes | |
| Reference Manual |
Details
| biocViews | Infrastructure, Microarray, OneChannel, Software |
| Version | 1.26.0 |
| In Bioconductor since | BioC 2.2 (R-2.7) |
| License | Artistic-2.0 |
| Depends | R (>= 2.7.0), XML (>= 2.8-1), RCurl (>= 0.8-1), methods |
| Imports | Biostrings |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | IdMappingRetrieval |
| Suggests Me | oneChannelGUI |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | AffyCompatible_1.26.0.tar.gz |
| Windows Binary | AffyCompatible_1.26.0.zip |
| Mac OS X 10.6 (Snow Leopard) | AffyCompatible_1.26.0.tgz |
| Mac OS X 10.9 (Mavericks) | AffyCompatible_1.26.0.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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