labelParams {Envisage} | R Documentation

## Remove labelling variables

### Description

This function removes any categorical variables which have the same number of levels as there are samples (labelling variables).

### Usage

      labelParams(pData)

### Arguments

`pData` | An object of class `phenoData` containing the phenotypic information for the experiment.

### Details

The Envisage package contains methods allowing the use of linear models (LMs) for analysing significantly changing genes in experiments with a variety of sources of variation, be they experimentally controlled variables such as drug treatment or time, or non-controlled sources of confounding variation such as phenotypic or environmental differences. This allows all sources of variation to be considered when analysing for significant differential expression, ensuring resulting genes are biologically relevent to the experimental question.

The function `labelParams` ensures that any categorical variables included by the user for model fitting that have the same number of factor levels as there are samples are removed prior to fitting the model. Such labelling variables contain a unique value for each sample, and will this result in a perfect fit for the data.

`labelParams` is an internal function and is not designed to be accessed by users.

### Value

A vector is returned containing the indices of the labelling parameters for the `phenoData` object `pData`.

### Author(s)

Sam Robson S.C.Robson@warwick.ac.uk

### References

Robson, S. C., Hunter, E., Bird, H., Turner, H. (2008) Envisage: model-based significance analysis of microarray gene expression data, manuscript in preparation

### See Also

For the main Envisage method, see `envisage`.

[Package Envisage version 1.0-2 Index]