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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("affxparser")
In most cases, you don't need to download the package archive at all.
affxparser
Affymetrix File Parsing SDK
Bioconductor version: 2.14
Package for parsing Affymetrix files (CDF, CEL, CHP, BPMAP, BAR). It provides methods for fast and memory efficient parsing of Affymetrix files using the Affymetrix' Fusion SDK. Both ASCII- and binary-based files are supported. Currently, there are methods for reading chip definition file (CDF) and a cell intensity file (CEL). These files can be read either in full or in part. For example, probe signals from a few probesets can be extracted very quickly from a set of CEL files into a convenient list structure.
Author: Henrik Bengtsson [aut], James Bullard [aut], Robert Gentleman [ctb], Kasper Daniel Hansen [aut, cre], Martin Morgan [ctb]
Maintainer: Kasper Daniel Hansen <khansen at jhsph.edu>
Citation (from within R,
enter citation("affxparser")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("affxparser")
Documentation
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | DataImport, Infrastructure, Software |
| Version | 1.36.0 |
| In Bioconductor since | BioC 1.7 (R-2.2) |
| License | LGPL (>= 2) |
| Depends | R (>= 2.6.0) |
| Imports | |
| Suggests | R.utils (>= 1.29.8), AffymetrixDataTestFiles |
| System Requirements | |
| URL | |
| Depends On Me | ITALICS, pdInfoBuilder, rMAT, Starr |
| Imports Me | affyILM, AffyTiling, cn.farms, GeneRegionScan, ITALICS, oligo, rMAT |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | affxparser_1.36.0.tar.gz |
| Windows Binary | affxparser_1.36.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | affxparser_1.36.0.tgz |
| Mac OS X 10.9 (Mavericks) | affxparser_1.36.0.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
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