Package: acde 1.35.0

Juan Pablo Acosta

acde: Artificial Components Detection of Differentially Expressed Genes

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).

Authors:Juan Pablo Acosta, Liliana Lopez-Kleine

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NEWS

# Install 'acde' in R:
install.packages('acde', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • phytophthora - Gene Expression Data for Tomato Plants Inoculated with _Phytophthora infestans_

On BioConductor:acde-1.35.0(bioc 3.20)acde-1.34.0(bioc 3.19)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

bioconductor-package

7 exports 0.82 score 1 dependencies

Last updated 2 months agofrom:b6f5b768f0

Exports:acac2bcaFDRfdrqvalstptc

Dependencies:boot

Identification of Differentially Expressed Genes with Artificial Components

Rendered fromacde.Rnwusingutils::Sweaveon Jun 24 2024.

Last update: 2015-05-24
Started: 2015-05-11