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factDesign (version 1.48.0)

Factorial designed microarray experiment analysis

Description

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.

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Version

Version

1.48.0

License

LGPL

Maintainer

Denise Scholtens

Last Published

February 15th, 2017

Functions in factDesign (1.48.0)

outliers

Detect single outliers in experimental designs with only two replicates per treatment condition.
findFC

A function to find the fold change between two experimental conditions in a factorial experiment based on the linear model parameter estimates.
estrogen

Microarray Data from an Experiment on Breast Cancer Cells
kRepsOverA

A filter function for at least k sets of replicates in a factorial experiment to have mean larger than A.
contrasts

Construct appropriate lambda matrix and test linear contrasts of the parameter estimates from a linear model.