Per-credible-set summary of a fine-mapping result

One row per credible set (at a given coverage) with its size, purity, prior variance, log Bayes factor, and lead variant – the per-CS complement to the per-variant credibleSets. Replaces the legacy per-effect `effect.tsv`.

Usage

credibleSetSummary(x, ...)

# S4 method for class 'FineMappingResultBase'
credibleSetSummary(x, coverage = 0.95)

Arguments

x

A QtlFineMappingResult or GwasFineMappingResult.

...

Ignored.

coverage

Credible-set coverage to summarise. Default 0.95.

Value

A tibble: cs, effect_id, coverage, n_variants, purity_min, purity_mean, V, cs_log10bf (strongest member logBF), cs_log_bf (true per-effect single-effect log Bayes factor), cs_pip (summed member PIP = inclusion mass captured), cs_mean_effect (mean posterior conditional effect), lead_variant, lead_pip (the collection method also carries the entry identity columns).

See also

credibleSets, topLoci

Examples

data(qtlFineMappingExample)
credibleSetSummary(qtlFineMappingExample)
#> # A tibble: 1 × 21
#>   study   context   trait  blockId method dataType dataSource standardized cs   
#>   <chr>   <chr>     <chr>  <chr>   <chr>  <chr>    <chr>      <chr>        <chr>
#> 1 study_1 context_1 gene_1 NA      susie  NA       NA         NA           susi…
#> # ℹ 12 more variables: effect_id <chr>, coverage <dbl>, n_variants <int>,
#> #   purity_min <dbl>, purity_mean <dbl>, V <dbl>, cs_log10bf <dbl>,
#> #   cs_log_bf <dbl>, cs_pip <dbl>, cs_mean_effect <dbl>, lead_variant <chr>,
#> #   lead_pip <dbl>