calculate_transcript_mc {transite} | R Documentation

## Motif Enrichment calculation

### Description

C++ implementation of Motif Enrichment calculation

### Usage

    calculate_transcript_mc(
      absoluteHits,
      totalSites,
      relHitsForeground,
      n,
      maxPermutations,
      minPermutations,
      e
    )

### Arguments

`absoluteHits` | number of putative binding sites per sequence (returned by `score_transcripts`)
`totalSites` | number of potential binding sites per sequence (returned by `score_transcripts`)
`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 `e` random enrichment values with more extreme values than the actual enrichment value

### Value

list with p-value and number of iterations of Monte Carlo sampling for foreground enrichment

### Examples

    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)

[Package transite version 1.10.0 Index]