-
Notifications
You must be signed in to change notification settings - Fork 0
/
README.Rmd
68 lines (49 loc) · 2.43 KB
/
README.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
---
output: github_document
editor_options:
markdown:
wrap: 72
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE, warn = FALSE, message = FALSE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# phenotypeR <img src="man/figures/logo.png" align="right" height="180"/>
<!-- badges: start -->
> **This package is under development and not yet ready for use.**
[![R-CMD-check](https://github.com/ohdsi/phenotypeR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/ohdsi/phenotypeR/actions/workflows/R-CMD-check.yaml)
[![Lifecycle:Experimental](https://img.shields.io/badge/Lifecycle-Experimental-339999)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
<!-- badges: end -->
The phenotypeR package supports the assessment of cohorts
Codelist-level diagnostics help to answer questions like what concepts from our codelist are used in the database? What concepts were present led to individuals' entry in the cohort? Are there any concepts being used in the database that we didn't include in our codelist but maybe we should have?
Cohort-level diagnostics help to answer questions like how many individuals did we include in our cohort and how many were excluded because of our inclusion criteria? If we have multiple cohorts, is there overlap between them and when do people enter one cohort relative to another? What is the incidence of cohort entry and what is the prevalence of the cohort in the database? What are the characteristics of those people in the cohort, and how do they compare to people similar in terms of age and sex?
## Installation
You can install phenotypeR from GitHub:
```{r, eval = FALSE}
# install.packages("remotes")
remotes::install_github("oxford-pharmacoepi/phenotypeR")
```
## Codelist diagnostics
```{r, message=FALSE}
library(omopgenerics)
library(CDMConnector)
library(phenotypeR)
library(CohortConstructor)
library(dplyr)
con <- DBI::dbConnect(duckdb::duckdb(dbdir = CDMConnector::eunomia_dir()))
cdm <- CDMConnector::cdm_from_con(con = con,
cdm_schema = "main",
write_schema = "main")
cdm$gibleed <- conceptCohort(cdm = cdm,
conceptSet = list(gibleed = 192671L),
name = "gibleed")
result <- cdm$gibleed |>
phenotypeDiagnostics()
result |>
glimpse()
```