moderated_p_limma_long: Moderate p-value for long table

In wolski/prolfqua: Proteomics Label Free Quantification

Moderate p-value for long table

Description

Moderate p-value for long table

Usage

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

Arguments

mm	result of contrasts_linfct
group_by_col	colnames with contrast description - default 'lhs'

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(), 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()

Examples

mod <- build_models()
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 = my_contrast_V2)

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

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