| calculateTranscriptMC {transite} | R Documentation |
C++ implementation of Motif Enrichment calculation
calculateTranscriptMC(absoluteHits, totalSites, relHitsForeground, n, maxPermutations, minPermutations, e)
absoluteHits |
number of putative binding sites per sequence
(returned by |
totalSites |
number of potential binding sites per sequence
(returned by |
relHitsForeground |
relative number of hits in foreground set |
n |
number of sequences in the foreground set |
maxPermutations |
maximum number of foreground permutations performed in Monte Carlo test for enrichment score |
minPermutations |
minimum number of foreground permutations performed in Monte Carlo test for enrichment score |
e |
stop criterion for enrichment score Monte Carlo test:
aborting permutation process
after observing |
list with p-value and number of iterations of Monte Carlo sampling for foreground enrichment
foreground.seqs <- c("CAGUCAAGACUCC", "AAUUGGUUGUGGGGCUUCCCUGUACAU",
"AGAU", "CCAGUAA", "UGUGGGG")
background.seqs <- c(foreground.seqs, "CAACAGCCUUAAUU", "CUUUGGGGAAU",
"UCAUUUUAUUAAA", "AUCAAAUUA", "GACACUUAAAGAUCCU",
"UAGCAUUAACUUAAUG", "AUGGA", "GAAGAGUGCUCA",
"AUAGAC", "AGUUC")
motif.db <- getMotifById("M178_0.6")
fg <- scoreTranscripts(foreground.seqs, cache = FALSE,
motifs = motif.db)
bg <- scoreTranscripts(background.seqs, cache = FALSE,
motifs = motif.db)
mc.result <- calculateTranscriptMC(unlist(bg$absolute.hits),
unlist(bg$total.sites),
fg$df$absolute.hits / fg$df$total.sites,
length(foreground.seqs), 1000, 500, 5)