| eaBrowse {EnrichmentBrowser} | R Documentation |
Functions to extract a flat gene set ranking from an enrichment analysis result object and to detailedly explore it.
eaBrowse(res, nr.show = -1, graph.view = NULL, html.only = FALSE) gsRanking(res, signif.only = TRUE)
res |
Enrichment analysis result list (as returned by the functions
|
nr.show |
Number of gene sets to show. As default all statistically significant gene sets are displayed. |
graph.view |
Optional. Should a graph-based summary (reports and visualizes consistency of regulations) be created for the result? If specified, it needs to be a gene regulatory network, i.e. either an absolute file path to a tabular file or a character matrix with exactly *THREE* cols; 1st col = IDs of regulating genes; 2nd col = corresponding regulated genes; 3rd col = regulation effect; Use '+' and '-' for activation/inhibition. |
html.only |
Logical. Should the html file only be written (without opening the browser to view the result page)? Defaults to FALSE. |
signif.only |
Logical. Display only those gene sets in the ranking, which satisfy the significance level? Defaults to TRUE. |
gsRanking: DataFrame with gene sets ranked by
the corresponding p-value;
eaBrowse: none, opens the browser to explore results.
The main HTML report and associated files are written to
configEBrowser("OUTDIR.DEFAULT").
See ?configEBrowser to change the location.
If html.only=FALSE, the HTML report will automatically be opened in
the your default browser.
Ludwig Geistlinger <Ludwig.Geistlinger@sph.cuny.edu>
# real data
# (1) reading the expression data from file
exprs.file <- system.file("extdata/exprs.tab", package="EnrichmentBrowser")
cdat.file <- system.file("extdata/colData.tab", package="EnrichmentBrowser")
rdat.file <- system.file("extdata/rowData.tab", package="EnrichmentBrowser")
probeSE <- readSE(exprs.file, cdat.file, rdat.file)
geneSE <- probe2gene(probeSE)
geneSE <- deAna(geneSE)
metadata(geneSE)$annotation <- "hsa"
# artificial enrichment analysis results
gs <- makeExampleData(what="gs", gnames=names(geneSE))
ea.res <- makeExampleData(what="ea.res", method="ora", se=geneSE, gs=gs)
# (5) result visualization and exploration
gsRanking(ea.res)
eaBrowse(ea.res)