Package: daMA 1.77.0

Jobst Landgrebe

daMA: Efficient design and analysis of factorial two-colour microarray data

This package contains functions for the efficient design of factorial two-colour microarray experiments and for the statistical analysis of factorial microarray data. Statistical details are described in Bretz et al. (2003, submitted)

Authors:Jobst Landgrebe <[email protected]> and Frank Bretz <[email protected]>

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daMA/json (API)

# Install 'daMA' in R:
install.packages('daMA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • cinfo - Vector indexing the matrix cmat
  • cinfoB.AB - Vector indexing the matrix cmatB.AB
  • cmat - Contrast matrix describing the experimental questions
  • cmatB.AB - Contrast matrix describing the experimental questions
  • data.3x2 - 3x2 microarray data
  • designs.basic - Basic designs for two-colour factorial 3 x 2 microarray data
  • designs.composite - Composite designs for two-colour factorial 3 x 2 microarray data
  • id.3x2 - A vector of length 30012 containing numeric identifiers of the genes from the microarray dataset data.3x2.

On BioConductor:daMA-1.77.0(bioc 3.20)daMA-1.76.0(bioc 3.19)

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

bioconductor-package

9 exports 0.91 score 1 dependencies

Last updated 2 months agofrom:9eede9e891

Exports:analyseMAcinfocinfoB.ABcmatcmatB.ABcoredesignMAdesigns.basicdesigns.composite

Dependencies:MASS