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This is the development version of acde; for the stable release version, see acde.

Artificial Components Detection of Differentially Expressed Genes

Bioconductor version: Development (3.20)

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>

Citation (from within R, enter citation("acde")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Identification of Differentially Expressed Genes with Artificial Components PDF R Script
Reference Manual PDF


biocViews DifferentialExpression, GeneExpression, Microarray, PrincipalComponent, Software, TimeCourse, mRNAMicroarray
Version 1.35.0
In Bioconductor since BioC 3.2 (R-3.2) (9 years)
License GPL-3
Depends R (>= 3.3), boot (>= 1.3)
Imports stats, graphics
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