To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("acde")
In most cases, you don't need to download the package archive at all.
acde
|
Artificial Components Detection of Differentially Expressed Genes
Bioconductor version: 3.2
This package provides a multivariate inferential analysis method for detecting differentially expressed genes in gene expression data. It uses artificial components, close to the data's principal components but with an exact interpretation in terms of differential genetic expression, to identify differentially expressed genes while controlling the false discovery rate (FDR). The methods on this package are described in the vignette or in the article 'Multivariate Method for Inferential Identification of Differentially Expressed Genes in Gene Expression Experiments' by J. P. Acosta, L. Lopez-Kleine and S. Restrepo (2015, pending publication).
Author: Juan Pablo Acosta, Liliana Lopez-Kleine
Maintainer: Juan Pablo Acosta <jpacostar at unal.edu.co>
Citation (from within R,
enter citation("acde")):
Installation
To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("acde")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("acde")
| Identification of Differentially Expressed Genes with Artificial Components | ||
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | DifferentialExpression, GeneExpression, Microarray, PrincipalComponent, Software, TimeCourse, mRNAMicroarray |
| Version | 1.0.0 |
| In Bioconductor since | BioC 3.2 (R-3.2) (0.5 years) |
| License | GPL-3 |
| Depends | R (>= 3.2), boot (>= 1.3) |
| Imports | |
| LinkingTo | |
| Suggests | BiocGenerics, RUnit |
| 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 | acde_1.0.0.tar.gz |
| Windows Binary | acde_1.0.0.zip |
| Mac OS X 10.6 (Snow Leopard) | acde_1.0.0.tgz |
| Mac OS X 10.9 (Mavericks) | acde_1.0.0.tgz |
| Subversion source | (username/password: readonly) |
| Git source | https://github.com/Bioconductor-mirror/acde/tree/release-3.2 |
| Package Short Url | http://bioconductor.org/packages/acde/ |
| Package Downloads Report | Download Stats |
Documentation »
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