knitr, rmarkdown, ggpubr, graphics, emmeans, coin, boot,
testthat, spelling

'utilities.R' 'add_significance.R' 'adjust_pvalue.R'
'factorial_design.R' 'utilities_two_sample_test.R'
'anova_summary.R' 'anova_test.R' 'as_cor_mat.R' 'binom_test.R'
'box_m.R' 'chisq_test.R' 'cochran_qtest.R' 'cohens_d.R'
'cor_as_symbols.R' 'replace_triangle.R' 'pull_triangle.R'
'cor_mark_significant.R' 'cor_mat.R' 'cor_plot.R'
'cor_reorder.R' 'cor_reshape.R' 'cor_select.R' 'cor_test.R'
'counts_to_cases.R' 'cramer_v.R' 'df.R' 'doo.R' 't_test.R'
'dunn_test.R' 'emmeans_test.R' 'eta_squared.R' 'factors.R'
'fisher_test.R' 'freq_table.R' 'friedman_test.R'
'friedman_effsize.R' 'games_howell_test.R' 'get_comparisons.R'
'get_manova_table.R' 'get_mode.R' 'get_pvalue_position.R'
'get_summary_stats.R' 'get_test_label.R' 'kruskal_effesize.R'
'kruskal_test.R' 'levene_test.R' 'mahalanobis_distance.R'
'make_clean_names.R' 'mcnemar_test.R' 'multinom_test.R'
'outliers.R' 'p_value.R' 'prop_test.R' 'prop_trend_test.R'
'reexports.R' 'remove_ns.R' 'sample_n_by.R' 'shapiro_test.R'
'sign_test.R' 'tukey_hsd.R' 'utils-manova.R' 'utils-pipe.R'
'welch_anova_test.R' 'wilcox_effsize.R' 'wilcox_test.R'

person(given = "Kirill",
           family = "M\u00fcller",
           role = c("aut", "cre"),
           email = "kirill@cynkra.com",
           comment = c(ORCID = "0000-0002-1416-3412"))

Robust, reliable and flexible paths to files below
    a project root. The 'root' of a project is defined as a directory that
    matches a certain criterion, e.g., it contains a certain regular file.

covr, knitr, lifecycle, mockr, rlang, rmarkdown, testthat (>=
3.0.0), withr

Kirill Müller [aut, cre] (<https://orcid.org/0000-0002-1416-3412>)

Empirical Analysis of Digital Gene Expression Data in R

Differential expression analysis of RNA-seq expression profiles with biological replication. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models and quasi-likelihood tests. As well as RNA-seq, it be applied to differential signal analysis of other types of genomic data that produce read counts, including ChIP-seq, ATAC-seq, Bisulfite-seq, SAGE and CAGE.