estimate_significance: Permutation Test Based Significance of Observed Mean

In transite: RNA-binding protein motif analysis

Description

estimate_significance returns an estimate of the significance of the observed mean, given a set of random permutations of the data.

Usage

estimate_significance(
  actual_mean,
  motif_kmers,
  random_permutations,
  alternative = c("two_sided", "less", "greater"),
  conf_level = 0.95,
  produce_plot = TRUE
)

Arguments

actual_mean	observed mean
motif_kmers	set of k-mers that were used to compute the actual_mean
random_permutations	a set of random permutations of the original data, used to generate an empirical null distribution.
alternative	side of the test, one of the following: "two_sided", "less", "greater"
conf_level	confidence level for the returned confidence interval
produce_plot	if distribution plot should be part of the returned list

Value

A list with the following components:

p_value_estimate	the estimated p-value of the observed mean
conf_int	the confidence interval around that estimate
plot	plot of the empirical distribution of geometric means of the enrichment values

See Also

Other k-mer functions: calculate_kmer_enrichment(), check_kmers(), compute_kmer_enrichment(), count_homopolymer_corrected_kmers(), draw_volcano_plot(), estimate_significance_core(), generate_kmers(), generate_permuted_enrichments(), run_kmer_spma(), run_kmer_tsma()

transite documentation built on Nov. 8, 2020, 5:27 p.m.