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R6 class for limma modelling strategy

Source: R/ContrastsLimma.R
StrategyLimma.Rd

R6 class for limma modelling strategy

R6 class for limma modelling strategy

Details

Analogous to strategy_lm but for limma's matrix-based pipeline. Consumed by build_model_limma.

See also

Other modelling: AnovaExtractor, Contrasts, ContrastsDEqMSFacade, ContrastsFirth, ContrastsFirthFacade, ContrastsLMFacade, ContrastsLMImputeFacade, ContrastsLMMissingFacade, ContrastsLimma, ContrastsLimmaFacade, ContrastsLmerFacade, ContrastsMissing, ContrastsModerated, ContrastsModeratedDEqMS, ContrastsPlotter, ContrastsRLMFacade, ContrastsROPECA, ContrastsROPECAFacade, ContrastsTable, INTERNAL_FUNCTIONS_BY_FAMILY, LR_test(), Model, ModelFirth, ModelLimma, StrategyLM, StrategyLmer, StrategyLogistf, StrategyRLM, build_contrast_analysis(), build_model(), build_model_glm_peptide(), build_model_glm_protein(), build_model_impute(), build_model_limma(), build_model_logistf(), compute_borrowed_variance(), 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(), moderated_p_limma_long(), my_contest(), my_contrast(), my_contrast_V2(), 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_logistf(), summary_ROPECA_median_p.scaled()

Public fields

formula

model formula

model_name

name of model

trend

logical, passed to eBayes

robust

logical, passed to eBayes

weights

either a character string (column name) or a numeric matrix

Methods

Public methods

Method new()

Create a new StrategyLimma

Usage

StrategyLimma$new(
  modelstr,
  model_name = "limma",
  trend = FALSE,
  robust = FALSE,
  weights = NULL
)

Arguments

modelstr

model formula as string (e.g. "abundance ~ group_")

model_name

name of model

trend

logical, passed to eBayes

robust

logical, passed to eBayes

weights

either a character string (column name in annotation for per-sample weights) or a numeric matrix (proteins x samples) passed to lmFit. Default NULL (no weights).

Method clone()

The objects of this class are cloneable with this method.

Usage

StrategyLimma$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.