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p-value of protein from p.value of the median fold change peptide.

Source: R/tidyMS_moderation.R
get_p_values_pbeta.Rd

p-value of protein from p.value of the median fold change peptide.

Usage

get_p_values_pbeta(median.p.value, n.obs, max.n = 10)

Arguments

max.n

limit number of peptides per protein.

See also

Other modelling: AnovaExtractor, Contrasts, ContrastsDEqMSFacade, ContrastsDEqMSVoomFacade, ContrastsFirth, ContrastsFirthFacade, ContrastsLMFacade, ContrastsLMImputeFacade, ContrastsLMMissingFacade, ContrastsLimma, ContrastsLimmaFacade, ContrastsLimmaImputeFacade, ContrastsLimmaVoomFacade, ContrastsLimmaVoomImputeFacade, ContrastsLimpaFacade, ContrastsLmerFacade, ContrastsMissing, ContrastsModerated, ContrastsModeratedDEqMS, ContrastsPlotter, ContrastsRLMFacade, ContrastsROPECA, ContrastsROPECAFacade, ContrastsTable, INTERNAL_FUNCTIONS_BY_FAMILY, LR_test(), Model, ModelFirth, ModelLimma, StrategyLM, StrategyLimma, StrategyLimpa, StrategyLmer, StrategyLogistf, StrategyRLM, build_contrast_analysis(), build_model(), build_model_glm_peptide(), build_model_glm_protein(), build_model_impute(), build_model_limma(), build_model_limma_impute(), build_model_limma_voom(), build_model_limma_voom_impute(), build_model_limpa(), build_model_logistf(), compute_borrowed_variance(), compute_borrowed_variance_limma(), compute_contrast(), compute_lmer_contrast(), contrasts_fisher_exact(), get_anova_df(), get_complete_model_fit(), group_label(), impute_refit_singular(), isSingular_lm(), linfct_all_possible_contrasts(), linfct_factors_contrasts(), linfct_from_model(), linfct_matrix_contrasts(), merge_contrasts_results(), model_analyse(), model_summary(), moderated_p_deqms(), moderated_p_deqms_long(), moderated_p_limma(), moderated_p_limma_long(), new_lm_imputed(), pivot_model_contrasts_2_Wide(), plot_lmer_peptide_predictions(), sim_build_models_lm(), sim_build_models_lmer(), sim_build_models_logistf(), sim_make_model_lm(), sim_make_model_lmer(), strategy_limma(), strategy_limpa(), strategy_logistf(), summary_ROPECA_median_p.scaled()

Examples

plot(get_p_values_pbeta(0.1,1:10,10), ylim=c(0,0.1))

plot(get_p_values_pbeta(0.1,1:10,3), ylim=c(0,0.1))

plot(get_p_values_pbeta(0.3,1:30, 3), ylim=c(0,0.1))
abline(h=.05,col = 2)

plot(seq(0.0,1.0,length=30),get_p_values_pbeta(seq(0.0,1.0,length=30),rep(10,30)))
abline(0,1)

plot(seq(0.0,1.0,length=30),get_p_values_pbeta(seq(0.0,1.0,length=30),rep(10,30),3))
abline(0,1)

testthat::expect_equal(get_p_values_pbeta(0.3,10, 3),0.216, tolerance = 1e-4)
testthat::expect_equal(get_p_values_pbeta(0,10, 3),0, tolerance = 1e-4)
testthat::expect_equal(get_p_values_pbeta(1,10, 3),1, tolerance = 1e-4)
testthat::expect_equal(get_p_values_pbeta(1,10, 3),get_p_values_pbeta(1,3, 10), tolerance = 1e-4)