moderated_p_limma: Moderate p-values - limma approach

In wolski/prolfqua: Proteomics Label Free Quantification

Moderate p-values - limma approach

Description

Moderate p-values - limma approach

Usage

moderated_p_limma(
  mm,
  df = "df",
  estimate = "diff",
  robust = FALSE,
  confint = 0.95
)

See Also

Other modelling: Contrasts, ContrastsMissing, ContrastsModerated, ContrastsPlotter, ContrastsProDA, ContrastsROPECA, ContrastsTable, INTERNAL_FUNCTIONS_BY_FAMILY, LR_test(), Model, build_model(), build_models(), contrasts_fisher_exact(), get_anova_df(), get_complete_model_fit(), get_p_values_pbeta(), isSingular_lm(), linfct_all_possible_contrasts(), linfct_factors_contrasts(), linfct_from_model(), linfct_matrix_contrasts(), make_model(), merge_contrasts_results(), model_analyse(), model_summary(), moderated_p_limma_long(), my_contest(), my_contrast(), my_contrast_V1(), my_contrast_V2(), my_glht(), pivot_model_contrasts_2_Wide(), plot_lmer_model_and_data(), plot_lmer_peptide_noRandom(), plot_lmer_peptide_predictions(), plot_lmer_predicted_interactions(), strategy_lmer(), summary_ROPECA_median_p.scaled()

wolski/prolfqua documentation built on May 12, 2024, 10:16 p.m.