calculate_motif_enrichment: Binding Site Enrichment Value Calculation

In kkrismer/transite: RNA-binding protein motif analysis

Binding Site Enrichment Value Calculation

Description

This function is used to calculate binding site enrichment / depletion scores between predefined foreground and background sequence sets. Significance levels of enrichment values are obtained by Monte Carlo tests.

Usage

calculate_motif_enrichment(
  foreground_scores_df,
  background_scores_df,
  background_total_sites,
  background_absolute_hits,
  n_transcripts_foreground,
  max_fg_permutations = 1e+06,
  min_fg_permutations = 1000,
  e = 5,
  p_adjust_method = "BH"
)

Arguments

foreground_scores_df	result of score_transcripts on foreground sequence set (foreground sequence sets must be a subset of the background sequence set)
background_scores_df	result of score_transcripts on background sequence set
background_total_sites	number of potential binding sites per sequence (returned by score_transcripts)
background_absolute_hits	number of putative binding sites per sequence (returned by score_transcripts)
n_transcripts_foreground	number of sequences in the foreground set
max_fg_permutations	maximum number of foreground permutations performed in Monte Carlo test for enrichment score
min_fg_permutations	minimum number of foreground permutations performed in Monte Carlo test for enrichment score
e	integer-valued 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
p_adjust_method	adjustment of p-values from Monte Carlo tests to avoid alpha error accumulation, see p.adjust

Value

A data frame with the following columns:

motif_id	the motif identifier that is used in the original motif library
motif_rbps	the gene symbol of the RNA-binding protein(s)
enrichment	binding site enrichment between foreground and background sequences
p_value	unadjusted p-value from Monte Carlo test
p_value_n	number of Monte Carlo test permutations
adj_p_value	adjusted p-value from Monte Carlo test (usually FDR)

See Also

Other matrix functions: run_matrix_spma(), run_matrix_tsma(), score_transcripts(), score_transcripts_single_motif()

Examples

foreground_seqs <- c("CAGUCAAGACUCC", "AAUUGGUGUCUGGAUACUUCCCUGUACAU",
  "AGAU", "CCAGUAA")
background_seqs <- c(foreground_seqs, "CAACAGCCUUAAUU", "CUUUGGGGAAU",
                     "UCAUUUUAUUAAA", "AUCAAAUUA", "GACACUUAAAGAUCCU",
                     "UAGCAUUAACUUAAUG", "AUGGA", "GAAGAGUGCUCA",
                     "AUAGAC", "AGUUC")
foreground_scores <- score_transcripts(foreground_seqs, cache = FALSE)
background_scores <- score_transcripts(background_seqs, cache = FALSE)
enrichments_df <- calculate_motif_enrichment(foreground_scores$df,
  background_scores$df,
  background_scores$total_sites, background_scores$absolute_hits,
  length(foreground_seqs),
  max_fg_permutations = 1000
)

kkrismer/transite documentation built on July 13, 2024, 8:01 a.m.