Up- and down-regulated genes in modules based on limma object
For each module in mset and for each coefficient in f$coefficients, this function calculates the numbers of significantly up- and down-regulated genes.
tmodLimmaDecideTests( f, genes, lfc.thr = 0.5, pval.thr = 0.05, filter.unknown = FALSE, adjust.method = "BH", mset = "all" )
result of linear model fit produced by limma functions lmFit and eBayes
Either the name of the column in f$genes which contains the gene symbols corresponding to the gene set collection used, or a character vector with gene symbols
log fold change threshold
If TRUE, modules with no annotation will be omitted
method used to adjust the p-values for multiple testing. See p.adjust(). Default:BH.
Which module set to use (see tmodUtest for details)
A list with as many elements as there were coefficients in f. Each element of the list is a data frame with the columns "Down", "Zero" and "Up" giving the number of the down-, not- and up-regulated genes respectively. Rows of the data frame correspond to module IDs. The object can directly be used in tmodPanelPlot as the pie parameter.
For an f object returned by eBayes(), tmodLimmaDecideTests considers every coefficient in this model (every column of f$coefficients). For each such coefficient, tmodLimmaDecideTests calculates, for each module, the number of genes which are up- or down-regulated.
In short, tmodLimmaDecideTests is the equivalent of tmodDecideTests, but for limma objects returned by eBayes().