GlobalAncova.closed {GlobalAncova} | R Documentation |
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.
There are three possible ways of using GlobalAncova
.
Also GlobalAncova.closed
can be invoked with these three alternatives.
## S4 method for signature 'matrix, list, formula, formula, ## ANY, missing, missing, missing': GlobalAncova.closed(xx, test.genes, previous.test, level, formula.full, formula.red, model.dat, perm = 10000) ## S4 method for signature 'matrix, list, formula, missing, ## ANY, missing, missing, character': GlobalAncova.closed(xx, test.genes, previous.test, level, formula.full, test.terms, model.dat, perm = 10000) ## S4 method for signature 'matrix, list, missing, missing, ## missing, numeric, ANY, missing': GlobalAncova.closed(xx, test.genes, previous.test, level, group, covars = NULL, perm = 10000)
xx |
Matrix of gene expression data, where columns correspond to samples
and rows to genes. The data should be properly normalized beforehand
(and log- or otherwise transformed). Missing values are not allowed.
Gene and sample names can be included as the row and column
names of xx . |
test.genes |
A list of pathways that shall be tested, each containing vectors of gene names. |
previous.test |
The output of a call to GlobalAncova with specified option
test.genes according to the pathways of interest. |
level |
The global level of significance of the testing procedure. |
formula.full |
Model formula for the full model. |
formula.red |
Model formula for the reduced model (that does not contain the terms of interest). |
model.dat |
Data frame that contains all the variable information for each sample. |
group |
Vector with the group membership information. |
covars |
Vector or matrix which contains the covariate information for each sample. |
test.terms |
Character vector that contains names of the terms of interest. |
perm |
Number of permutations to be used. The default is 10,000. |
A list with components
new.data |
Family of null hypotheses (vectors of genes to be tested simultaneously with GlobalAncova ). |
test.results |
Test results for each pathway of interest and all hypotheses included in it. |
significant |
Names of the significant pathways. |
not.significant |
Names of the non significant pathways. |
xx
and the list of gene groups
test.genes
, model formulas for the full
and reduced model and a data frame model.dat
specifying corresponding model
terms have to be given. Terms that are included in the full but not in the reduced
model are those whose association with differential expression will be tested.
The arguments group
, covars
and test.terms
are '"missing"'
since they are not needed for this method.xx
and the list of gene groups
test.genes
, a model formula for the full
model and a data frame model.dat
specifying corresponding model
terms are required. The character argument test.terms
names the terms of interest
whose association with differential expression will be tested.
The arguments formula.red
, group
and covars
are '"missing"'
since they are not needed for this method.xx
and the list of gene groups
test.genes
a clinical variable group
is
required. Covariate adjustment is possible via the argument covars
but
more complex models have to be specified with the methods described above.
This method emulates the function call in the first version of the package.
The arguments formula.full
, formula.red
, model.dat
and
test.terms
are '"missing"' since they are not needed for this method.This work was supported by the NGFN project 01 GR 0459, BMBF, Germany.
Reinhard Meister meister@tfh-berlin.de
Ulrich Mansmann mansmann@ibe.med.uni-muenchen.de
Manuela Hummel hummel@ibe.med.uni-muenchen.de
Marcus, R., Peritz, E. and Gabriel, K.R., 1976, On closed testing procedures with special reference to ordered analysis of variance, Biometrika 63 (3): 655–660.
GlobalAncova
, Plot.genes
, Plot.subjects