Collect differential-abundance results in a tidy contract

tidy_results() combines the results of executed differential-abundance steps without changing the engine-specific tables stored in rec@results. Effect sizes are labelled with their engine-specific metric and must not be compared directly across incompatible metrics.

Usage

tidy_results(rec, steps = steps_ids(rec, "da"), significant_only = FALSE)

Arguments

rec

A PrepRecipe object.

steps

Character vector of executed differential-abundance step IDs to collect. By default, all executed DA steps are included.

significant_only

If TRUE, retain only rows classified as significant by their originating step.

Value

A deterministic tibble with one row per taxon, contrast and configured step. It contains taxon identifiers (taxa_id, taxa), contrast metadata (contrast_id, comparison, contrast_type, var, numerator, denominator, at_var, at_level), statistics (effect_size, effect_metric, p_value, adj_p_value, significant), the stable engine in method, and the configured instance in step_id.

Examples

data(test_prep_rec)
results <- tidy_results(test_prep_rec)
results
#> # A tibble: 312 × 17
#>    taxa_id taxa             contrast_id comparison contrast_type var   numerator
#>    <chr>   <chr>            <chr>       <chr>      <chr>         <chr> <chr>    
#>  1 Otu_1   Methanobrevibac… RiskGroup2… RiskGroup… main          Risk… msm      
#>  2 Otu_10  Bifidobacterium  RiskGroup2… RiskGroup… main          Risk… msm      
#>  3 Otu_34  Olsenella        RiskGroup2… RiskGroup… main          Risk… msm      
#>  4 Otu_35  Collinsella      RiskGroup2… RiskGroup… main          Risk… msm      
#>  5 Otu_39  Enorma           RiskGroup2… RiskGroup… main          Risk… msm      
#>  6 Otu_45  Slackia          RiskGroup2… RiskGroup… main          Risk… msm      
#>  7 Otu_78  Bacteroides      RiskGroup2… RiskGroup… main          Risk… msm      
#>  8 Otu_82  Barnesiella      RiskGroup2… RiskGroup… main          Risk… msm      
#>  9 Otu_86  Butyricimonas    RiskGroup2… RiskGroup… main          Risk… msm      
#> 10 Otu_88  Odoribacter      RiskGroup2… RiskGroup… main          Risk… msm      
#> # ℹ 302 more rows
#> # ℹ 10 more variables: denominator <chr>, at_var <chr>, at_level <chr>,
#> #   effect_size <dbl>, effect_metric <chr>, p_value <dbl>, adj_p_value <dbl>,
#> #   significant <lgl>, method <chr>, step_id <chr>

tidy_results(test_prep_rec, significant_only = TRUE)
#> # A tibble: 62 × 17
#>    taxa_id taxa            contrast_id  comparison contrast_type var   numerator
#>    <chr>   <chr>           <chr>        <chr>      <chr>         <chr> <chr>    
#>  1 Otu_35  Collinsella     RiskGroup2[… RiskGroup… main          Risk… msm      
#>  2 Otu_78  Bacteroides     RiskGroup2[… RiskGroup… main          Risk… msm      
#>  3 Otu_82  Barnesiella     RiskGroup2[… RiskGroup… main          Risk… msm      
#>  4 Otu_86  Butyricimonas   RiskGroup2[… RiskGroup… main          Risk… msm      
#>  5 Otu_88  Odoribacter     RiskGroup2[… RiskGroup… main          Risk… msm      
#>  6 Otu_94  Paraprevotella  RiskGroup2[… RiskGroup… main          Risk… msm      
#>  7 Otu_96  Prevotella      RiskGroup2[… RiskGroup… main          Risk… msm      
#>  8 Otu_119 Alistipes       RiskGroup2[… RiskGroup… main          Risk… msm      
#>  9 Otu_125 Parabacteroides RiskGroup2[… RiskGroup… main          Risk… msm      
#> 10 Otu_259 Coprococcus     RiskGroup2[… RiskGroup… main          Risk… msm      
#> # ℹ 52 more rows
#> # ℹ 10 more variables: denominator <chr>, at_var <chr>, at_level <chr>,
#> #   effect_size <dbl>, effect_metric <chr>, p_value <dbl>, adj_p_value <dbl>,
#> #   significant <lgl>, method <chr>, step_id <chr>