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DEqMS contrast analysis facade

Source: R/ContrastsFacades.R
ContrastsDEqMSFacade.Rd

DEqMS contrast analysis facade

DEqMS contrast analysis facade

Details

Encapsulates the pipeline: strategy_lm -> build_model -> Contrasts -> merge with ContrastsMissing -> ContrastsModeratedDEqMS.

See also

Other modelling: AnovaExtractor, Contrasts, 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(), moderated_p_limma_long(), 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()

Public fields

model

Model object

contrast

ContrastsModeratedDEqMS object

.lfqdata

stored reference to input LFQData

.contrast_names

names of the requested contrasts

Methods

Public methods

Method new()

initialize

Usage

ContrastsDEqMSFacade$new(
  lfqdata,
  modelstr,
  contrasts,
  weights = lfqdata$config$nr_children,
  ...
)

Arguments

lfqdata

LFQData object

modelstr

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

contrasts

named character vector of contrasts

weights

column name for per-observation weights (default: lfqdata$config$nr_children). Pass NULL for unweighted.

...

passed to strategy_lm

Method get_contrasts()

get contrast results

Usage

ContrastsDEqMSFacade$get_contrasts(...)

Arguments

...

passed to ContrastsModeratedDEqMS$get_contrasts

Method get_missing()

get protein × contrast pairs that could not be estimated

Usage

ContrastsDEqMSFacade$get_missing()

Method get_Plotter()

get ContrastsPlotter

Usage

ContrastsDEqMSFacade$get_Plotter(...)

Arguments

...

passed to ContrastsModeratedDEqMS$get_Plotter

Method to_wide()

convert results to wide format

Usage

ContrastsDEqMSFacade$to_wide(...)

Arguments

...

passed to ContrastsModeratedDEqMS$to_wide

Method clone()

The objects of this class are cloneable with this method.

Usage

ContrastsDEqMSFacade$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

istar <- sim_lfq_data_protein_config(Nprot = 50)
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
lfqdata <- LFQData$new(istar$data, istar$config)
lfqdata$rename_response("transformedIntensity")
contrasts <- c("A_vs_Ctrl" = "group_A - group_Ctrl")
fa <- ContrastsDEqMSFacade$new(lfqdata, "~ group_", contrasts)
head(fa$get_contrasts())
#> determine linear functions:
#> get_contrasts -> contrasts_linfct
#> contrasts_linfct
#> Joining with `by = join_by(protein_Id, contrast)`
#> Warning: moderated_p_deqms_long: warnings in 1/1 groups. contrast=A_vs_Ctrl (pseudoinverse used at 1; neighborhood radius 1; reciprocal condition number  2.362e-17)
#> # A tibble: 6 × 14
#>   facade contrast  modelName  protein_Id   diff std.error avgAbd statistic    df
#>   <chr>  <chr>     <chr>      <chr>       <dbl>     <dbl>  <dbl>     <dbl> <int>
#> 1 deqms  A_vs_Ctrl WaldTest_… 0EfVhX~71…  3.00      0.886   18.8     4.77      6
#> 2 deqms  A_vs_Ctrl WaldTest_… 0m5WN4~35…  0.222     0.912   20.4     0.342     8
#> 3 deqms  A_vs_Ctrl WaldTest_… 76k03k~97…  0.509     0.464   19.9     0.825     9
#> 4 deqms  A_vs_Ctrl WaldTest_… 7QuTub~55… -1.22      0.874   23.4    -1.57      8
#> 5 deqms  A_vs_Ctrl WaldTest_… 7cbcrd~04…  1.38      0.690   16.5     1.35      3
#> 6 deqms  A_vs_Ctrl WaldTest_… 7soopj~34…  0.822     0.617   25.9     1.13      9
#> # ℹ 5 more variables: p.value <dbl>, conf.low <dbl>, conf.high <dbl>,
#> #   sigma <dbl>, FDR <dbl>
fa$to_wide()
#> Warning: moderated_p_deqms_long: warnings in 1/1 groups. contrast=A_vs_Ctrl (pseudoinverse used at 1; neighborhood radius 1; reciprocal condition number  2.362e-17)
#> # A tibble: 49 × 5
#>    protein_Id diff.A_vs_Ctrl p.value.A_vs_Ctrl FDR.A_vs_Ctrl statistic.A_vs_Ctrl
#>    <chr>               <dbl>             <dbl>         <dbl>               <dbl>
#>  1 0EfVhX~71…          3.00            0.00310         0.152               4.77 
#>  2 0m5WN4~35…          0.222           0.741           0.816               0.342
#>  3 76k03k~97…          0.509           0.431           0.816               0.825
#>  4 7QuTub~55…         -1.22            0.154           0.584              -1.57 
#>  5 7cbcrd~04…          1.38            0.271           0.705               1.35 
#>  6 7soopj~34…          0.822           0.288           0.705               1.13 
#>  7 9VUkAq~86…         -1.95            0.0232          0.228              -2.80 
#>  8 At886V~03…         -0.290           0.806           0.823              -0.279
#>  9 BEJI92~54…          0.961           0.232           0.669               1.31 
#> 10 CGzoYe~12…         -2.10            0.00867         0.175              -3.34 
#> # ℹ 39 more rows