
Collect differential-abundance results in a tidy contract
Source:R/result-contract.R
tidy_results.Rdtidy_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: 448 × 17
#> taxa_id taxa contrast_id comparison contrast_type var numerator
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Otu_1 Methanobrevibac… RiskGroup2… hts_msm legacy_pairw… Risk… NA
#> 2 Otu_10 Bifidobacterium RiskGroup2… hts_msm legacy_pairw… Risk… NA
#> 3 Otu_18 Bifidobacterium RiskGroup2… hts_msm legacy_pairw… Risk… NA
#> 4 Otu_34 Olsenella RiskGroup2… hts_msm legacy_pairw… Risk… NA
#> 5 Otu_35 Collinsella RiskGroup2… hts_msm legacy_pairw… Risk… NA
#> 6 Otu_37 Collinsella RiskGroup2… hts_msm legacy_pairw… Risk… NA
#> 7 Otu_39 Enorma RiskGroup2… hts_msm legacy_pairw… Risk… NA
#> 8 Otu_45 Slackia RiskGroup2… hts_msm legacy_pairw… Risk… NA
#> 9 Otu_46 Bacteroides RiskGroup2… hts_msm legacy_pairw… Risk… NA
#> 10 Otu_47 Bacteroides RiskGroup2… hts_msm legacy_pairw… Risk… NA
#> # ℹ 438 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: 101 × 17
#> taxa_id taxa contrast_id comparison contrast_type var numerator
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Otu_35 Collinsella RiskGroup2[hts_… hts_msm legacy_pairw… Risk… NA
#> 2 Otu_37 Collinsella RiskGroup2[hts_… hts_msm legacy_pairw… Risk… NA
#> 3 Otu_46 Bacteroides RiskGroup2[hts_… hts_msm legacy_pairw… Risk… NA
#> 4 Otu_47 Bacteroides RiskGroup2[hts_… hts_msm legacy_pairw… Risk… NA
#> 5 Otu_51 Bacteroides RiskGroup2[hts_… hts_msm legacy_pairw… Risk… NA
#> 6 Otu_52 Bacteroides RiskGroup2[hts_… hts_msm legacy_pairw… Risk… NA
#> 7 Otu_62 Bacteroides RiskGroup2[hts_… hts_msm legacy_pairw… Risk… NA
#> 8 Otu_69 Bacteroides RiskGroup2[hts_… hts_msm legacy_pairw… Risk… NA
#> 9 Otu_76 Bacteroides RiskGroup2[hts_… hts_msm legacy_pairw… Risk… NA
#> 10 Otu_77 Bacteroides RiskGroup2[hts_… hts_msm legacy_pairw… Risk… NA
#> # ℹ 91 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>