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Moderate p-value for long table

Source: R/tidyMS_moderation.R
moderated_p_limma_long.Rd

Moderate p-value for long table

Usage

moderated_p_limma_long(
  contrast_df,
  group_by_col = "lhs",
  estimate = "estimate",
  robust = FALSE
)

Arguments

contrast_df

result of contrasts_linfct

group_by_col

colnames with contrast description - default 'lhs'

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(), get_p_values_pbeta(), 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(), 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


mod <- sim_build_models_lm()
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
m <- get_complete_model_fit(mod$modelDF)
factor_contrasts <- linfct_factors_contrasts(m$linear_model[[1]])
factor_levelContrasts <- contrasts_linfct(
  mod$modelDF,
  factor_contrasts,
  subject_Id = "protein_Id",
  contrastfun = compute_contrast)
#> contrasts_linfct

mmm <- moderated_p_limma_long(factor_levelContrasts, group_by_col = "lhs")