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'))

Peer review:

Datasets:
  • estrogen - Microarray Data from an Experiment on Breast Cancer Cells

On BioConductor:factDesign-1.81.0(bioc 3.20)factDesign-1.80.0(bioc 3.19)

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 280 downloads 6 exports 2 dependencies

Last updated 23 days agofrom:f7b7be73bc. Checks:OK: 1 NOTE: 1 ERROR: 5. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winERROROct 30 2024
R-4.5-linuxNOTEOct 30 2024
R-4.4-winERROROct 30 2024
R-4.4-macERROROct 30 2024
R-4.3-winERROROct 30 2024
R-4.3-macERROROct 30 2024

Exports:contrastTestfindFCkRepsOverAmadOutPairoutlierPairpar2lambda

Dependencies:BiobaseBiocGenerics

factDesign

Rendered fromfactDesign.Rnwusingutils::Sweaveon Oct 30 2024.

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