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acde

Artificial Components Detection of Differentially Expressed Genes

Bioconductor version: 3.23 · Package version: 1.42.0

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).

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("acde")

Details

MaintainerJuan Pablo Acosta <jpacostar@unal.edu.co>
AuthorJuan Pablo Acosta, Liliana Lopez-Kleine
LicenseGPL-3
Downloads rank570
Source branchRELEASE_3_23
biocViewsDifferentialExpression, GeneExpression, Microarray, PrincipalComponent, Software, TimeCourse, mRNAMicroarray

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packageacde_1.42.0.tar.gz
Windows binary (x86_64)acde_1.42.0.zip
macOS binary (arm64)acde_1.42.0.tgz
macOS binary (x86_64)acde_1.42.0.tgz
Dependencies

Depends: R (>= 3.3), boot (>= 1.3)

Imports: stats, graphics

Suggests: BiocGenerics, RUnit