plot_credible_intervals {ppcseq} | R Documentation

## plot_credible interval for theoretical data distributions

### Description

Plot the data along the theoretical data distribution.

### Usage

    plot_credible_intervals(.data)

### Arguments

`.data` | The tibble returned by identify_outliers

### Value

A tibble with an additional `plot` column

### Examples

    library(dplyr)

    data("counts")

    if(Sys.info()[['sysname']] == "Linux"){
    result =
      counts %>%
      dplyr::mutate(  is_significant = ifelse(symbol %in% c("SLC16A12", "CYP1A1", "ART3"), TRUE, FALSE) ) %>%
     ppcseq::identify_outliers(
    	formula = ~ Label,
    	sample, symbol, value,
    	.significance = PValue,
    	.do_check  = is_significant,
    	percent_false_positive_genes = 1,
    	tol_rel_obj = 0.01,
    	approximate_posterior_inference =TRUE,
    	approximate_posterior_analysis =TRUE,
    	how_many_negative_controls = 50,
    	cores=1
    )

    result_plot = result %>% plot_credible_intervals()
    }

[Package ppcseq version 1.2.0 Index]