Package: factDesign 1.83.0
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:
factDesign_1.83.0.tar.gz
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factDesign.pdf |factDesign.html✨
factDesign/json (API)
# Install 'factDesign' in R: |
install.packages('factDesign', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- 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
Last updated 23 days agofrom:f7b7be73bc. Checks:OK: 1 NOTE: 1 ERROR: 5. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 30 2024 |
R-4.5-win | ERROR | Oct 30 2024 |
R-4.5-linux | NOTE | Oct 30 2024 |
R-4.4-win | ERROR | Oct 30 2024 |
R-4.4-mac | ERROR | Oct 30 2024 |
R-4.3-win | ERROR | Oct 30 2024 |
R-4.3-mac | ERROR | Oct 30 2024 |
Exports:contrastTestfindFCkRepsOverAmadOutPairoutlierPairpar2lambda
Dependencies:BiobaseBiocGenerics