GlobalAncova

Calculates a global test for differential gene expression between groups

We give the following arguments in support of the GlobalAncova approach: After appropriate normalisation, gene-expression-data appear rather symmetrical and outliers are no real problem, so least squares should be rather robust. ANCOVA with interaction yields saturated data modelling e.g. different means per group and gene. Covariate adjustment can help to correct for possible selection bias. Variance homogeneity and uncorrelated residuals cannot be expected. Application of ordinary least squares gives unbiased, but no longer optimal estimates (Gauss-Markov-Aitken). Therefore, using the classical F-test is inappropriate, due to correlation. The test statistic however mirrors deviations from the null hypothesis. In combination with a permutation approach, empirical significance levels can be approximated. Alternatively, an approximation yields asymptotic p-values. This work was supported by the NGFN grant 01 GR 0459, BMBF, Germany.

Author U. Mansmann, R. Meister, M. Hummel, R. Scheufele, with contributions from S. Knueppel
Maintainer R. Meister

To install this package, start R and enter:

    source("http://bioconductor.org/biocLite.R")
    biocLite("GlobalAncova")

Documentation

GlobalAncova PDF R Script
GlobalAncovaDecomp PDF R Script
Reference Manual

Details

biocViews
Depends
methods , corpcor , globaltest
Imports
Suggests
System Requirements
License GPL Version 2 or newer
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Development History Bioconductor Changelog

Package Downloads

Package source GlobalAncova_3.10.0.tar.gz
Windows binary GlobalAncova_3.10.0.zip
MacOS X 10.4 (Tiger) binary GlobalAncova_3.10.0.tgz
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