calculate_transcript_mc {transite} | R Documentation |
C++ implementation of Motif Enrichment calculation
calculate_transcript_mc( 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 <- get_motif_by_id("M178_0.6") fg <- score_transcripts(foreground_seqs, cache = FALSE, motifs = motif_db) bg <- score_transcripts(background_seqs, cache = FALSE, motifs = motif_db) mc_result <- calculate_transcript_mc(unlist(bg$absolute_hits), unlist(bg$total_sites), fg$df$absolute_hits / fg$df$total_sites, length(foreground_seqs), 1000, 500, 5)