Package: factDesign 1.88.0

Denise Scholtens

factDesign: Factorial designed microarray experiment analysis

This package provides a set of tools for analyzing data from a factorial designed microarray experiment, or any microarray experiment for which a linear model is appropriate. The functions can be used to evaluate tests of contrast of biological interest and perform single outlier detection.

Authors:Denise Scholtens

factDesign_1.88.0.tar.gz
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factDesign_1.88.0.tgz(r-4.6-any)factDesign_1.88.0.tgz(r-4.5-any)
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factDesign_1.88.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
factDesign/json (API)

# Install 'factDesign' in R:
install.packages('factDesign', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • estrogen - Microarray Data from an Experiment on Breast Cancer Cells

On BioConductor:factDesign-1.89.0(bioc 3.24)factDesign-1.88.0(bioc 3.23)

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

microarraydifferentialexpression

3.30 score 1 scripts 419 downloads 6 exports 3 dependencies

Last updated from:8221d18d69 (on RELEASE_3_23). Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
bioc-checksERROR129
linux-devel-x86_64NOTE174
source / vignettesOK158
linux-release-x86_64NOTE146
macos-release-arm64NOTE125
macos-oldrel-arm64NOTE71
windows-develNOTE90
windows-releaseNOTE73
windows-oldrelNOTE69
wasm-releaseOK113

Exports:contrastTestfindFCkRepsOverAmadOutPairoutlierPairpar2lambda

Dependencies:BiobaseBiocGenericsgenerics

factDesign

Rendered fromfactDesign.Rnwusingutils::Sweaveon May 29 2026.

Last update: 2013-11-01
Started: 2013-11-01