acde

DOI: 10.18129/B9.bioc.acde    

This package is for version 3.12 of Bioconductor; for the stable, up-to-date release version, see acde.

Artificial Components Detection of Differentially Expressed Genes

Bioconductor version: 3.12

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 (version "4.0") and enter:

if (!requireNamespace("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")

 

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

Details

biocViews DifferentialExpression, GeneExpression, Microarray, PrincipalComponent, Software, TimeCourse, mRNAMicroarray
Version 1.20.0
In Bioconductor since BioC 3.2 (R-3.2) (5.5 years)
License GPL-3
Depends R (>= 3.3), boot (>= 1.3)
Imports stats, graphics
LinkingTo
Suggests BiocGenerics, RUnit
SystemRequirements
Enhances
URL
Depends On Me
Imports Me coexnet
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package acde_1.20.0.tar.gz
Windows Binary acde_1.20.0.zip
macOS 10.13 (High Sierra) acde_1.20.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/acde
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/acde
Package Short Url https://bioconductor.org/packages/acde/
Package Downloads Report Download Stats

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