shinyDiagnostics: Create a shiny app summarising your phenotyping results

In PhenotypeR: Assess Study Cohorts Using a Common Data Model

Create a shiny app summarising your phenotyping results

Description

A shiny app that is designed for any diagnostics results from phenotypeR, this includes:

* A diagnostics on the database via 'databaseDiagnostics'. * A diagnostics on the cohort_codelist attribute of the cohort via 'codelistDiagnostics'. * A diagnostics on the cohort via 'cohortDiagnostics'. * A diagnostics on the population via 'populationDiagnostics'. * A diagnostics on the matched cohort via 'matchedDiagnostics'.

Usage

shinyDiagnostics(
  result,
  directory,
  minCellCount = 5,
  open = rlang::is_interactive(),
  expectations = NULL
)

Arguments

result	A summarised result
directory	Directory where to save report
minCellCount	Minimum cell count for suppression when exporting results.
open	If TRUE, the shiny app will be launched in a new session. If FALSE, the shiny app will be created but not launched.
expectations	Data frame or tibble with cohort expectations. It must contain the following columns: cohort_name, estimate, value, and source.

Value

A shiny app

Examples

library(PhenotypeR)
library(dplyr)

cdm <- mockPhenotypeR()

result <- phenotypeDiagnostics(cdm$my_cohort)
expectations <- tibble("cohort_name" = rep(c("cohort_1", "cohort_2"),3),
                       "value" = c(rep(c("Mean age"),2),
                                   rep("Male percentage",2),
                                   rep("Survival probability after 5y",2)),
                       "estimate" = c("32", "54", "25%", "74%", "95%", "21%"),
                       "source" = rep(c("AlbertAI"),6))

shinyDiagnostics(result, tempdir(), expectations = expectations)

CDMConnector::cdmDisconnect(cdm = cdm)

PhenotypeR documentation built on Aug. 8, 2025, 6:30 p.m.