Limpa contrast analysis facade for nested input

Limpa contrast analysis facade for nested input

Limpa contrast analysis facade for nested input

Value

An R6 class generator.

Details

Encapsulates the full precursor -> protein pipeline: AggregateLimpa -> strategy_limpa -> build_model_limpa -> ContrastsLimma.

Takes nested (precursor/peptide-level) LFQData, runs limpa's DPC-based aggregation internally to produce protein-level expression with posterior standard errors, then fits a vooma model with imputation-aware precision weights.

For protein-level input that was already aggregated upstream via AggregateLimpa, use ContrastsLimpaFacade instead.

See also

Other modelling: AnovaExtractor, Contrasts, ContrastsDEqMSFacade, ContrastsDEqMSVoomFacade, ContrastsFirth, ContrastsFirthFacade, ContrastsFirthNestedFacade, ContrastsLMFacade, ContrastsLMImputeFacade, ContrastsLMMissingFacade, ContrastsLimma, ContrastsLimmaFacade, ContrastsLimmaImputeFacade, ContrastsLimmaVoomFacade, ContrastsLimmaVoomImputeFacade, ContrastsLimpaFacade, ContrastsLmerNestedFacade, ContrastsMissing, ContrastsModerated, ContrastsModeratedDEqMS, ContrastsPlotter, ContrastsRLMFacade, ContrastsROPECA, ContrastsROPECANestedFacade, 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(), is_singular_lm(), linfct_all_possible_contrasts(), linfct_factors_contrasts(), linfct_from_model(), linfct_matrix_contrasts(), list_facades(), lookup_facade(), 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_to_wide(), plot_lmer_peptide_predictions(), register_facade(), 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(), unregister_facade()

Super class

prolfqua::ContrastsInterface -> ContrastsLimpaNestedFacade

Public fields

model

ModelLimma object (from build_model_limpa)

contrast

ContrastsLimma object

.lfqdata

stored reference to the aggregated protein-level LFQData

.lfqdata_nested

stored reference to the original nested input

.contrast_names

names of the requested contrasts

Methods

Public methods

• ContrastsLimpaNestedFacade$new()

• ContrastsLimpaNestedFacade$get_contrasts()

• ContrastsLimpaNestedFacade$get_missing()

• ContrastsLimpaNestedFacade$get_Plotter()

• ContrastsLimpaNestedFacade$to_wide()

• ContrastsLimpaNestedFacade$clone()

Inherited methods

• prolfqua::ContrastsInterface$column_description()
• prolfqua::ContrastsInterface$contrast_summary_table()
• prolfqua::ContrastsInterface$extra_artifacts()
• prolfqua::ContrastsInterface$filter_significant()
• prolfqua::ContrastsInterface$get_config()
• prolfqua::ContrastsInterface$get_contrast_sides()
• prolfqua::ContrastsInterface$get_ora()
• prolfqua::ContrastsInterface$get_rank()

---

Method new()

initialize

Usage

ContrastsLimpaNestedFacade$new(
  lfqdata,
  modelstr,
  contrasts,
  prefix = "protein",
  dpc_slope = 0.8,
  plot = FALSE,
  span = NULL,
  ...
)

Arguments

lfqdata

nested LFQData (precursor/peptide-level, log2-transformed)

modelstr

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

contrasts

named character vector of contrasts

prefix

prefix for the aggregated hierarchy level (default "protein")

dpc_slope

DPC slope parameter passed to AggregateLimpa (default 0.8)

plot

logical; if TRUE, plot the vooma mean-variance trend

span

lowess smoother span (NULL = auto)

...

passed to strategy_limpa (e.g. trend, robust)

---

Method get_contrasts()

get contrast results (rows with NA diff are filtered out)

Usage

ContrastsLimpaNestedFacade$get_contrasts(...)

Arguments

...

passed to ContrastsLimma$get_contrasts

---

Method get_missing()

get protein x contrast pairs that could not be estimated

Usage

ContrastsLimpaNestedFacade$get_missing()

---

Method get_Plotter()

get ContrastsPlotter

Usage

ContrastsLimpaNestedFacade$get_Plotter(...)

Arguments

...

passed to ContrastsLimma$get_Plotter

---

Method to_wide()

convert results to wide format

Usage

ContrastsLimpaNestedFacade$to_wide(...)

Arguments

...

passed to ContrastsLimma$to_wide

---

Method clone()

The objects of this class are cloneable with this method.

Usage

ContrastsLimpaNestedFacade$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

if (requireNamespace("limpa", quietly = TRUE)) {
  istar <- prolfqua::sim_lfq_data_peptide_config(Nprot = 10)
  lfqdata <- LFQData$new(istar$data, istar$config)
  lfqdata <- lfqdata$get_Transformer()$log2()$lfq
  contrasts <- c("A_vs_Ctrl" = "group_A - group_Ctrl")
  fa <- ContrastsLimpaNestedFacade$new(lfqdata, "~ group_", contrasts)
  head(fa$get_contrasts())
}
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
#> Column added : log2_abundance
#> # A tibble: 6 × 14
#>   facade       modelName protein_Id contrast    diff     FDR std.error statistic
#>   <chr>        <chr>     <chr>      <chr>      <dbl>   <dbl>     <dbl>     <dbl>
#> 1 limpa_nested limpa     0EfVhX~00… A_vs_Ct… -0.0244 4.07e-1    0.0283    -0.862
#> 2 limpa_nested limpa     7cbcrd~57… A_vs_Ct…  0.725  4.58e-3    0.185      3.91 
#> 3 limpa_nested limpa     9VUkAq~47… A_vs_Ct… -0.572  2.76e-4    0.0991    -5.78 
#> 4 limpa_nested limpa     BEJI92~52… A_vs_Ct…  0.236  1.38e-2    0.0739     3.19 
#> 5 limpa_nested limpa     CGzoYe~21… A_vs_Ct… -0.296  1.46e-1    0.175     -1.70 
#> 6 limpa_nested limpa     DoWup2~58… A_vs_Ct…  0.282  8.89e-5    0.0417     6.77 
#> # ℹ 6 more variables: p.value <dbl>, sigma <dbl>, df <dbl>, conf.low <dbl>,
#> #   conf.high <dbl>, avgAbd <dbl>