acde
This package is for version 3.19 of Bioconductor; for the stable, up-to-date release version, see acde.
Artificial Components Detection of Differentially Expressed Genes
Bioconductor version: 3.19
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("acde")
):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("acde")
For older versions of R, please refer to the appropriate Bioconductor release.
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 | R Script | |
Reference Manual | ||
NEWS | Text |
Details
biocViews | DifferentialExpression, GeneExpression, Microarray, PrincipalComponent, Software, TimeCourse, mRNAMicroarray |
Version | 1.34.0 |
In Bioconductor since | BioC 3.2 (R-3.2) (9 years) |
License | GPL-3 |
Depends | R (>= 3.3), boot (>= 1.3) |
Imports | stats, graphics |
System Requirements | |
URL |
See More
Suggests | BiocGenerics, RUnit |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | acde_1.34.0.tar.gz |
Windows Binary (x86_64) | acde_1.34.0.zip |
macOS Binary (x86_64) | acde_1.34.0.tgz |
macOS Binary (arm64) | acde_1.34.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/acde |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/acde |
Bioc Package Browser | https://code.bioconductor.org/browse/acde/ |
Package Short Url | https://bioconductor.org/packages/acde/ |
Package Downloads Report | Download Stats |