Description Usage Arguments Value See Also
estimate_significance
returns an estimate of the significance
of the observed
mean, given a set of random permutations of the data.
1 2 3 4 5 6 7 8 | estimate_significance(
actual_mean,
motif_kmers,
random_permutations,
alternative = c("two_sided", "less", "greater"),
conf_level = 0.95,
produce_plot = TRUE
)
|
actual_mean |
observed mean |
motif_kmers |
set of k-mers that were used to compute
the |
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:
|
conf_level |
confidence level for the returned confidence interval |
produce_plot |
if distribution plot should be part of the returned list |
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 |
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()
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