pair.compare: Pairwise comparisons of factor levels within GlobalAncova
In GlobalAncova: Global test for groups of variables via model comparisons

Description Usage Arguments Value Note Author(s) See Also Examples

Pairwise comparisons of gene expression in different levels of a factor by GlobalAncova tests. The method uses the reduction in residual sum of squares obtained when two respective factor levels are set to the same level. Holm-adjusted permutation-based p-values are given.

1	pair.compare(xx, formula, group, model.dat = NULL, test.genes = 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`.
`formula`	Model formula for the linear model.
`group`	Factor for which pairwise comparisons shall be calculated.
`model.dat`	Data frame that contains all the variable information for each sample.
`test.genes`	Vector of gene names or a list where each element is a vector of gene names.
`perm`	Number of permutations to be used for the permutation approach. The default is 10,000.

An ANOVA table, or list of ANOVA tables for each gene set, for the pairwise comparisons.

This work was supported by the NGFN project 01 GR 0459, BMBF, Germany.

Ramona Scheufele ramona.scheufele@charite.de
Reinhard Meister meister@tfh-berlin.de
Manuela Hummel m.hummel@dkfz.de
Urlich Mansmann mansmann@ibe.med.uni-muenchen.de

GlobalAncova, GlobalAncova.decomp

data(vantVeer)
data(phenodata)
data(pathways)

pair.compare(xx = vantVeer, formula = ~ grade, group = "grade", model.dat = phenodata, test.genes = pathways[1:3], perm = 100)

Loading required package: corpcor
Loading required package: globaltest
Loading required package: survival
$androgen_receptor_signaling
             SSQ   df         MS         F p.perm
1 : 2   2.688551   72 0.03734099 0.9669613   0.48
1 : 3   8.252015   72 0.11461131 2.9679105   0.00
2 : 3  12.524917   72 0.17395718 4.5046979   0.00
error 258.578336 6696 0.03861684        NA     NA

$apoptosis
             SSQ    df         MS         F p.perm
1 : 2   5.487855   187 0.02934682 0.8294273   0.67
1 : 3  13.842299   187 0.07402299 2.0921072   0.03
2 : 3  18.591096   187 0.09941763 2.8098343   0.00
error 615.328795 17391 0.03538202        NA     NA

$cell_cycle_control
             SSQ   df         MS        F p.perm
1 : 2   1.864403   31 0.06014204 1.343001   0.19
1 : 3   9.602664   31 0.30976336 6.917169   0.00
2 : 3   9.136795   31 0.29473533 6.581586   0.00
error 129.105956 2883 0.04478181       NA     NA