runLOLA {LOLA} | R Documentation |
Workhorse function that calculates overlaps between userSets, and then uses a fisher's exact test rank them by significance of the overlap.
runLOLA( userSets, userUniverse, regionDB, minOverlap = 1, cores = 1, redefineUserSets = FALSE, direction = "enrichment" )
userSets |
Regions of interest |
userUniverse |
Regions tested for inclusion in userSets |
regionDB |
Region DB to check for overlap, from loadRegionDB() |
minOverlap |
(Default:1) Minimum bases required to count an overlap |
cores |
Number of processors |
redefineUserSets |
run redefineUserSets() on your userSets? |
direction |
Defaults to "enrichment", but may also accept "depletion", which will swap the direction of the fisher test (use 'greater' or less' value passed to the 'alternative' option of fisher.test) |
Data.table with enrichment results. Rows correspond to individual pairwise fisher's tests comparing a single userSet with a single databaseSet. The columns in this data.table are: userSet and dbSet: index into their respective input region sets. pvalueLog: -log10(pvalue) from the fisher's exact result; oddsRatio: result from the fisher's exact test; support: number of regions in userSet overlapping databaseSet; rnkPV, rnkOR, rnkSup: rank in this table of p-value, oddsRatio, and Support respectively. The –value is the negative natural log of the p-value returned from a one-sided fisher's exact test. maxRnk, meanRnk: max and mean of the 3 previous ranks, providing a combined ranking system. b, c, d: 3 other values completing the 2x2 contingency table (with support). The remaining columns describe the dbSet for the row.
If you have the qvalue package installed from bioconductor, runLOLA will add a q-value transformation to provide FDR scores automatically.
dbPath = system.file("extdata", "hg19", package="LOLA") regionDB = loadRegionDB(dbLocation=dbPath) data("sample_universe", package="LOLA") data("sample_input", package="LOLA") getRegionSet(regionDB, collections="ucsc_example", filenames="vistaEnhancers.bed") getRegionSet(dbPath, collections="ucsc_example", filenames="vistaEnhancers.bed") getRegionFile(dbPath, collections="ucsc_example", filenames="vistaEnhancers.bed") res = runLOLA(userSets, userUniverse, regionDB, cores=1) locResult = res[2,] extractEnrichmentOverlaps(locResult, userSets, regionDB) writeCombinedEnrichment(locResult, "temp_outfolder") userSetsRedefined = redefineUserSets(userSets, userUniverse) resRedefined = runLOLA(userSetsRedefined, userUniverse, regionDB, cores=1) g = plotTopLOLAEnrichments(resRedefined)