Package: factDesign 1.83.0

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

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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-1.83.0(bioc 3.21)factDesign-1.82.0(bioc 3.20)

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 328 downloads 6 exports 3 dependencies

Last updated 4 months agofrom:f7b7be73bc. Checks:1 OK, 6 NOTE, 1 ERROR. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 31 2025
R-4.5-winNOTEJan 31 2025
R-4.5-macERRORJan 31 2025
R-4.5-linuxNOTEJan 31 2025
R-4.4-winNOTEJan 31 2025
R-4.4-macNOTEJan 31 2025
R-4.3-winNOTEJan 31 2025
R-4.3-macNOTEJan 31 2025

Exports:contrastTestfindFCkRepsOverAmadOutPairoutlierPairpar2lambda

Dependencies:BiobaseBiocGenericsgenerics

factDesign

Rendered fromfactDesign.Rnwusingutils::Sweaveon Jan 31 2025.

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