Bioconductor version: Release (3.16)
The association between a variable of interest (e.g. two groups) and the global pattern of a group of variables (e.g. a gene set) is tested via a global F-test. 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. The framework is generalized to groups of categorical variables or even mixed data by a likelihood ratio approach. Closed and hierarchical testing procedures are supported. This work was supported by the NGFN grant 01 GR 0459, BMBF, Germany and BMBF grant 01ZX1309B, Germany.
Author: U. Mansmann, R. Meister, M. Hummel, R. Scheufele, with contributions from S. Knueppel
Maintainer: Manuela Hummel <manuela.hummel at web.de>
Citation (from within R,
enter citation("GlobalAncova")
):
To install this package, start R (version "4.2") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("GlobalAncova")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("GlobalAncova")
R Script | GlobalAncova.pdf | |
R Script | GlobalAncovaDecomp.pdf | |
Reference Manual | ||
Text | NEWS |
biocViews | DifferentialExpression, Microarray, OneChannel, Pathways, Regression, Software |
Version | 4.16.0 |
In Bioconductor since | BioC 1.7 (R-2.2) (17.5 years) |
License | GPL (>= 2) |
Depends | methods, corpcor, globaltest |
Imports | annotate, AnnotationDbi, Biobase, dendextend, GSEABase, VGAM |
LinkingTo | |
Suggests | GO.db, golubEsets, hu6800.db, vsn, Rgraphviz |
SystemRequirements | |
Enhances | |
URL | |
Depends On Me | |
Imports Me | miRtest |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | GlobalAncova_4.16.0.tar.gz |
Windows Binary | GlobalAncova_4.16.0.zip |
macOS Binary (x86_64) | GlobalAncova_4.16.0.tgz |
macOS Binary (arm64) | |
Source Repository | git clone https://git.bioconductor.org/packages/GlobalAncova |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/GlobalAncova |
Bioc Package Browser | https://code.bioconductor.org/browse/GlobalAncova/ |
Package Short Url | https://bioconductor.org/packages/GlobalAncova/ |
Package Downloads Report | Download Stats |
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