plotClusteredEnrichment: plotClusteredEnrichment
In robertsehlke/SETHRO: Simple Enrichment Testing for Highly Redundant Ontologies

Description Usage Arguments Author(s) Examples

Simple barplot that displays the enrichment of primary gene sets from a clusteredEnrichment result.

plotClusteredEnrichment(ceresult, alpha = 0.05, t.alpha = 0.05,
  max_bars = NULL, top_n = Inf, only_positive_enrichment = T,
  order_by_enrichment = T, main = "Enriched primary gene sets",
  legend.title = "", xlim = NULL, lab_max_chars = 50, ...)

`ceresult`	$results data frame returned by the clusteredEnrichmentGO() function.
`alpha`	Significance cutoff for primary gene set adjusted p-values, defaults to 0.05.
`t.alpha`	If a directionality bias has been determined via t-test on the log-fold-change of the gene set, which significance cutoff should be used for the display of that bias? (i.e. bar color)
`max_bars`	If set, scales the bar plot to provide space for max_bars... bars. Use to ensure uniform scaling when plotting multiple results with varying numbers of significant hits.
`top_n`	Plot only the most significant top_n results. Default is to show all results.
`only_positive_enrichment`	Defaults to TRUE: show only positive log-enrichments (i.e. no depleted terms).
`order_by_enrichment`	Defaults to TRUE: order significant hits by effect magnitude (enrichment) rather than significance.
`legend.title`	Title of the legend (only relevant if directionality bias of GO terms is included in the results).
`xlim`	Axis limit of the enrichment plot. Use to ensure uniform axis across multiple plots.
`lab_max_chars`	Maximum length of gene set names; longer names are truncated.

Robert Sehlke

## Not run: 
# example for annotation matrix creation
# may be used interchangably with createGoMatrix()
gomatrix = createAnnotationMatrix( list("GO:0000042"=paste0("gene",1:6),
                                           "GO:0000002"=paste0("gene",2:7),
                                           "GO:0000009"=paste0("gene",6:12)) )

# example call for main function
res = clusteredEnrichmentGO(gomatrix, 
                            geneset = paste0("gene",2:6),
                            universe = paste0("gene",1:12))

# example plot
plotClusteredEnrichment(res$results)

## End(Not run)