Quasibinomial detection-count facade for nested input

Quasibinomial detection-count facade for nested input

Quasibinomial detection-count facade for nested input

Value

An R6 class generator.

Details

Completes and encodes child-feature detection using the same preparation as ContrastsFirthNestedFacade, then collapses the binary rows into detected and undetected counts per parent and sample. The resulting quasibinomial model reports parent-level log odds ratios in diff; avgAbd is the average linear predictor on the log-odds scale.

Child features are treated as exchangeable binomial trials. The symmetric pseudo-count stabilizes complete separation but is not equivalent to Firth's bias-reducing penalty. Empirical-Bayes dispersion moderation uses ContrastsModerated; by default posterior dispersion is bounded below by one.

Super classes

prolfqua::ContrastsInterface -> prolfqua::ContrastsFacadeBase -> ContrastsBinomialNestedFacade

Methods

Public methods

• ContrastsBinomialNestedFacade$new()

• ContrastsBinomialNestedFacade$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()
• prolfqua::ContrastsFacadeBase$get_Plotter()
• prolfqua::ContrastsFacadeBase$get_contrasts()
• prolfqua::ContrastsFacadeBase$get_missing()
• prolfqua::ContrastsFacadeBase$to_wide()

---

Method new()

Fit the nested detection-count model and its contrasts.

Usage

ContrastsBinomialNestedFacade$new(
  lfqdata,
  modelstr,
  contrasts,
  prior_count = 0.1,
  binomial_bound = TRUE,
  ...
)

Arguments

lfqdata

nested LFQData

modelstr

right-hand-side model formula

contrasts

named contrast expressions

prior_count

non-negative symmetric pseudo-count

binomial_bound

bound posterior dispersion below by one

...

passed to strategy_binomial

---

Method clone()

The objects of this class are cloneable with this method.

Usage

ContrastsBinomialNestedFacade$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

istar <- sim_lfq_data_peptide_config(Nprot = 20, weight_missing = 0.5, seed = 3)
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
lfqdata <- LFQData$new(istar$data, istar$config)
contrasts <- c("A_vs_Ctrl" = "group_A - group_Ctrl")
facade <- ContrastsBinomialNestedFacade$new(lfqdata, "~ group_", contrasts)
#> completing cases
head(facade$get_contrasts())
#> determine linear functions:
#> get_contrasts -> contrasts_linfct
#> contrasts_linfct
#> Joining with `by = join_by(protein_Id, contrast)`
#> # A tibble: 6 × 14
#>   modelName       estimate_type protein_Id  contrast       diff std.error avgAbd
#>   <chr>           <chr>         <chr>       <chr>         <dbl>     <dbl>  <dbl>
#> 1 binomial_nested observed      0GRprF~7339 A_vs_Ctrl -8.87e- 1  1.39e+ 0  0.444
#> 2 binomial_nested observed      4JK499~3111 A_vs_Ctrl  5.18e- 1  1.03e+ 0 -0.722
#> 3 binomial_nested observed      7IZdVV~6818 A_vs_Ctrl -5.85e- 1  7.54e- 1  1.34 
#> 4 binomial_nested observed      AZPG26~9461 A_vs_Ctrl  9.53e-16  1.41e-12  2.40 
#> 5 binomial_nested observed      AoNKbb~3497 A_vs_Ctrl -1.34e+ 0  1.60e+ 0  2.77 
#> 6 binomial_nested observed      CibL2O~2149 A_vs_Ctrl -1.47e+ 0  6.43e- 1 -0.733
#> # ℹ 7 more variables: statistic <dbl>, df <dbl>, p.value <dbl>, conf.low <dbl>,
#> #   conf.high <dbl>, sigma <dbl>, FDR <dbl>