Description Usage Arguments Value See Also Examples
estimate_significance_core returns an estimate of the significance
of the observed
mean, given a vector of means based on random permutations of the data.
1 2 3 4 5 6 | estimate_significance_core(
random_means,
actual_mean,
alternative = c("two_sided", "less", "greater"),
conf_level = 0.95
)
|
random_means |
numeric vector of means based on random permutations of the data (empirical null distribution) |
actual_mean |
observed mean |
alternative |
side of the test, one of the following:
|
conf_level |
confidence level for the returned confidence interval |
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 |
Other k-mer functions:
calculate_kmer_enrichment(),
check_kmers(),
compute_kmer_enrichment(),
count_homopolymer_corrected_kmers(),
draw_volcano_plot(),
estimate_significance(),
generate_kmers(),
generate_permuted_enrichments(),
run_kmer_spma(),
run_kmer_tsma()
1 2 3 4 | test_sd <- 1.0
test_null_distribution <- rnorm(n = 10000, mean = 1.0, sd = test_sd)
estimate_significance_core(test_null_distribution, test_sd * 2, "greater")
|
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