factDesign: Factorial designed microarray experiment analysis

Share:

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.

Author
Denise Scholtens
Date of publication
None
Maintainer
Denise Scholtens <dscholtens@northwestern.edu>
License
LGPL
Version
1.50.0

View on Bioconductor

Man pages

contrasts
Construct appropriate lambda matrix and test linear contrasts...
estrogen
Microarray Data from an Experiment on Breast Cancer Cells
findFC
A function to find the fold change between two experimental...
kRepsOverA
A filter function for at least k sets of replicates in a...
outliers
Detect single outliers in experimental designs with only two...

Files in this package

factDesign/DESCRIPTION
factDesign/NAMESPACE
factDesign/R
factDesign/R/contrastTest.R
factDesign/R/findFC.R
factDesign/R/kRepsOverA.R
factDesign/R/madOutPair.R
factDesign/R/outlierPair.R
factDesign/R/par2lambda.R
factDesign/build
factDesign/build/vignette.rds
factDesign/data
factDesign/data/estrogen.rda
factDesign/inst
factDesign/inst/doc
factDesign/inst/doc/factDesign.R
factDesign/inst/doc/factDesign.Rnw
factDesign/inst/doc/factDesign.pdf
factDesign/man
factDesign/man/contrasts.Rd
factDesign/man/estrogen.Rd
factDesign/man/findFC.Rd
factDesign/man/kRepsOverA.Rd
factDesign/man/outliers.Rd
factDesign/vignettes
factDesign/vignettes/factDesign.Rnw