plot_credible_intervals: plot_credible interval for theoretical data distributions

In stemangiola/ppcSeq: Probabilistic Outlier Identification for RNA Sequencing Generalized Linear Models

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()
}

stemangiola/ppcSeq documentation built on Sept. 19, 2023, 6:30 p.m.