GlobalAncova (version 3.40.0)

pair.compare: Pairwise comparisons of factor levels within GlobalAncova

Description

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.

Usage

pair.compare(xx, formula, group, model.dat = NULL, test.genes = NULL, perm = 10000)

Arguments

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.

Value

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

See Also

GlobalAncova, GlobalAncova.decomp

Examples

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

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

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