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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("antiProfiles")
In most cases, you don't need to download the package archive at all.
antiProfiles
Implementation of gene expression anti-profiles
Bioconductor version: 3.0
Implements gene expression anti-profiles as described in Corrada Bravo et al., BMC Bioinformatics 2012, 13:272 doi:10.1186/1471-2105-13-272.
Author: Hector Corrada Bravo, Rafael A. Irizarry and Jeffrey T. Leek
Maintainer: Hector Corrada Bravo <hcorrada at gmail.com>
Citation (from within R,
enter citation("antiProfiles")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("antiProfiles")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("antiProfiles")
| R Script | Introduction to antiProfiles | |
| Reference Manual |
Details
| biocViews | Classification, GeneExpression, Software |
| Version | 1.6.0 |
| In Bioconductor since | BioC 2.12 (R-3.0) |
| License | Artistic-2.0 |
| Depends | R (>= 3.0), matrixStats (>= 0.5), methods (>= 2.14) |
| Imports | |
| LinkingTo | |
| Suggests | antiProfilesData, 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 | antiProfiles_1.6.0.tar.gz |
| Windows Binary | antiProfiles_1.6.0.zip |
| Mac OS X 10.6 (Snow Leopard) | antiProfiles_1.6.0.tgz |
| Mac OS X 10.9 (Mavericks) | antiProfiles_1.6.0.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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