There are three possible ways of using GlobalAncova. The general way is to define formulas for the full and reduced model, respectively, where the formula terms correspond to variables in model.dat. An alternative is to specify the full model and the name of the model terms that shall be tested regarding differential expression. In order to make this layout compatible with the function call in the first version of the package there is also a method where simply a group variable (and possibly covariate information) has to be given. This is maybe the easiest usage in cases where no 'special' effects like e.g. interactions are of interest.
Computation of a F-test for the association between expression values and clinical entities. In many cases a two way layout with gene and a dichotomous group as factors will be considered. However, adjustment for other covariates and the analysis of arbitrary clinical variables, interactions, gene co-expression, time series data and so on is also possible. The test is carried out by comparison of corresponding linear models via the extra sum of squares principle. Corresponding p-values, permutation p-values and/or asymptotic p-values are given.
There are three possible ways of using GlobalAncova, use methods ? GlobalAncova for getting more information. Also GlobalAncova.closed can be invoked with these three alternatives.
GlobalAncova.closed
(Package: GlobalAncova) :
Closed testing procedure for testing several groups of genes using GlobalAncova
Computation of a closed testing procedure for several groups of genes, e.g. pathways, as an alternative of correcting for multiple testing. Starting from the pathways of interest a family of null hypotheses is created that is closed under intersection. Each null hypothesis can be rejected at a given level if it is rejected along with all hypotheses included in it.
GlobalAncova.decomp
(Package: GlobalAncova) :
GlobalAncova with sequential and type III sum of squares decomposition and adjustment for global covariates
Computation of a F-test for the association between expression values and clinical entities. The test is carried out by comparison of corresponding linear models via the extra sum of squares principle. In models with various influencing factors extra sums of squares can be treated with sequential and type III decomposition. Adjustment for global covariates, e.g. gene expression values in normal tissue as compared to tumour tissue, can be applied. Given theoretical p-values may not be appropriate due to correlations and non-normality. The functions are hence seen more as a descriptive tool.
There are three possible ways of using GlobalAncova, use methods ? GlobalAncova for getting more information. Also Plot.genes can be invoked with these three alternatives.
There are three possible ways of using GlobalAncova, use methods ? GlobalAncova for getting more information. Also Plot.subjects can be invoked with these three alternatives.
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