Package: factDesign 1.89.0

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_1.89.0.tar.gz
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factDesign_1.89.0.tgz(r-4.6-any)factDesign_1.89.0.tgz(r-4.5-any)
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manual.pdf |manual.html✨
card.svg |card.png
factDesign/json (API)

# Install 'factDesign' in R:
install.packages('factDesign', repos = c('https://bioc.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:a4d3c25cb9. Checks:1 ERROR, 6 NOTE, 2 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksERROR132
linux-devel-x86_64NOTE237
source / vignettesOK187
linux-release-x86_64FAIL1007
macos-release-arm64NOTE99
macos-oldrel-arm64NOTE111
windows-develNOTE86
windows-releaseNOTE68
windows-oldrelNOTE75
wasm-releaseOK95

Exports:contrastTestfindFCkRepsOverAmadOutPairoutlierPairpar2lambda

Dependencies:BiobaseBiocGenericsgenerics

factDesign

Rendered fromfactDesign.Rnwusingutils::Sweaveon Jun 10 2026.

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