mulTestCor {Envisage} | R Documentation

## Multiple testing corrections for package Envisage

### Description

This function corrects the p-values obtained from package Envisage to account for problems with multiple testing. These corrected p-values give a measure of the significance of model terms on the effects on gene expression changes for individual genes.

### Usage

      mulTestCor(pValues, MTC, pData, exprData, param4INT)

### Arguments

`pValues` | An object of class `data.frame` containing the p-values from the Type II sum of squares analysis for each model term for each gene.
`MTC` | A character string that defines which multiple testing correction method to use (if any). Available methods are `None`, `BH`, `BY`, `Bonferroni`, `Holm`, `Hochberg`, `SidakSS`, `SidakSD`. More information on these can be found in the package vignette. `BH` is selected by default.
`pData` | An object of class `phenoData` containing the phenotypic information for the experiment.
`exprData` | A matrix of expression values for each gene for each sample. Usually calculated using `exprs` on an object of class `ExpressionSet`.
`param4INT` | Character vector of variables for which interaction terms should be calculated.

### 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.

Due to the large number of genes analysed, gene expression analyses can suffer from problems due to multiple hypothesis testing. The function `mulTestCor` performs the selected multiple testing correction on the p-values indicating significance of each model term for each gene in the analysis.

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

### Value

An object of class `data.frame` is returned containing the adjusted p-values for each model term for each gene.

### 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]