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CohortGenerator

Cohort Generation for the OMOP Common Data Model

https://github.com/ohdsi/cohortgenerator

Science Score: 26.0%

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    Scientific vocabulary similarity
    Low similarity (12.2%) to scientific vocabulary

Keywords

hades
Last synced: 9 months ago · JSON representation

Repository

Cohort Generation for the OMOP Common Data Model

Basic Info
Statistics
  • Stars: 14
  • Watchers: 9
  • Forks: 14
  • Open Issues: 36
  • Releases: 17
Topics
hades
Created almost 5 years ago · Last pushed 10 months ago
Metadata Files
Readme Changelog

README.md

CohortGenerator

CRAN status Build Status codecov.io

CohortGenerator is part of HADES.

Introduction

This R package contains functions for generating cohorts and cohort subsets using data in the CDM.

Features

  • Create a cohort table and generate cohorts against an OMOP CDM.
  • Get the count of subjects and events in a cohort.
  • Define subsets of cohorts using different criteria or other cohorts.
  • Provides functions for performing incremental tasks. This is used by CohortGenerator to skip any cohorts that were successfully generated in a previous run. This functionality is generic enough for other packages to use for performing their own incremental tasks.

Example

``` r

First construct a cohort definition set: an empty

data frame with the cohorts to generate

cohortsToCreate <- CohortGenerator::createEmptyCohortDefinitionSet()

Fill the cohort set using cohorts included in this

package as an example

cohortJsonFiles <- list.files(path = system.file("testdata/name/cohorts", package = "CohortGenerator"), full.names = TRUE) for (i in 1:length(cohortJsonFiles)) { cohortJsonFileName <- cohortJsonFiles[i] cohortName <- tools::filepathsans_ext(basename(cohortJsonFileName)) # Here we read in the JSON in order to create the SQL # using CirceR # If you have your JSON and SQL stored differenly, you can # modify this to read your JSON/SQL files however you require cohortJson <- readChar(cohortJsonFileName, file.info(cohortJsonFileName)$size) cohortExpression <- CirceR::cohortExpressionFromJson(cohortJson) cohortSql <- CirceR::buildCohortQuery(cohortExpression, options = CirceR::createGenerateOptions(generateStats = FALSE)) cohortsToCreate <- rbind(cohortsToCreate, data.frame(cohortId = i, cohortName = cohortName, sql = cohortSql, stringsAsFactors = FALSE)) }

Generate the cohort set against Eunomia.

cohortsGenerated contains a list of the cohortIds

successfully generated against the CDM

connectionDetails <- Eunomia::getEunomiaConnectionDetails()

Create the cohort tables to hold the cohort generation results

cohortTableNames <- CohortGenerator::getCohortTableNames(cohortTable = "mycohorttable") CohortGenerator::createCohortTables(connectionDetails = connectionDetails, cohortDatabaseSchema = "main", cohortTableNames = cohortTableNames)

Generate the cohorts

cohortsGenerated <- CohortGenerator::generateCohortSet(connectionDetails = connectionDetails, cdmDatabaseSchema = "main", cohortDatabaseSchema = "main", cohortTableNames = cohortTableNames, cohortDefinitionSet = cohortsToCreate)

Get the cohort counts

cohortCounts <- CohortGenerator::getCohortCounts(connectionDetails = connectionDetails, cohortDatabaseSchema = "main", cohortTable = cohortTableNames$cohortTable) print(cohortCounts) ```

Technology

CohortGenerator is an R package.

System requirements

Requires R (version 3.6.0 or higher).

Getting Started

  1. Make sure your R environment is properly configured. This means that Java must be installed. See these instructions for how to configure your R environment.

  2. In R, use the following commands to download and install CohortGenerator:

    r remotes::install_github("OHDSI/CohortGenerator")

User Documentation

Documentation can be found on the package website.

PDF versions of the documentation are also available:

Support

Contributing

Read here how you can contribute to this package.

License

CohortGenerator is licensed under Apache License 2.0

Development

This package is being developed in RStudio.

Development status

Beta

Owner

  • Name: Observational Health Data Sciences and Informatics
  • Login: OHDSI
  • Kind: organization

GitHub Events

Total
  • Create event: 16
  • Release event: 2
  • Issues event: 22
  • Watch event: 2
  • Delete event: 8
  • Member event: 1
  • Issue comment event: 23
  • Push event: 140
  • Pull request review comment event: 15
  • Pull request review event: 17
  • Pull request event: 27
  • Fork event: 5
Last Year
  • Create event: 16
  • Release event: 2
  • Issues event: 22
  • Watch event: 2
  • Delete event: 8
  • Member event: 1
  • Issue comment event: 23
  • Push event: 140
  • Pull request review comment event: 15
  • Pull request review event: 17
  • Pull request event: 27
  • Fork event: 5

Issues and Pull Requests

Last synced: 9 months ago

All Time
  • Total issues: 88
  • Total pull requests: 122
  • Average time to close issues: 3 months
  • Average time to close pull requests: 26 days
  • Total issue authors: 20
  • Total pull request authors: 10
  • Average comments per issue: 1.67
  • Average comments per pull request: 0.94
  • Merged pull requests: 92
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 21
  • Pull requests: 33
  • Average time to close issues: 8 days
  • Average time to close pull requests: 3 days
  • Issue authors: 7
  • Pull request authors: 5
  • Average comments per issue: 0.19
  • Average comments per pull request: 0.27
  • Merged pull requests: 20
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • anthonysena (28)
  • azimov (13)
  • schuemie (10)
  • gowthamrao (10)
  • ablack3 (4)
  • chrisknoll (4)
  • ericaVoss (2)
  • catalamarti (2)
  • mdlavallee92 (2)
  • ob325 (2)
  • jreps (2)
  • edward-burn (1)
  • FredAC24 (1)
  • mgkahn (1)
  • jmb01 (1)
Pull Request Authors
  • anthonysena (86)
  • azimov (24)
  • FredAC24 (4)
  • gowthamrao (2)
  • mdlavallee92 (1)
  • javier-gracia-tabuenca-tuni (1)
  • mgkahn (1)
  • chrisknoll (1)
  • schuemie (1)
  • ablack3 (1)
Top Labels
Issue Labels
bug (3) enhancement (3) good first issue (3) help wanted (2) documentation (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 551 last-month
  • Total docker downloads: 245
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 4
  • Total maintainers: 1
cran.r-project.org: CohortGenerator

Cohort Generation for the OMOP Common Data Model

  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 551 Last month
  • Docker Downloads: 245
Rankings
Dependent packages count: 28.2%
Dependent repos count: 34.8%
Average: 49.9%
Downloads: 86.7%
Maintainers (1)
sena@ohdsi.org
Last synced: 9 months ago

Dependencies

.github/workflows/R_CMD_check_Hades.yaml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • actions/create-release v1 composite
  • actions/download-artifact v2 composite
  • actions/upload-artifact v2 composite
  • r-lib/actions/setup-pandoc v1 composite
  • r-lib/actions/setup-r v1 composite
  • r-lib/actions/setup-tinytex v1 composite
.github/workflows/R_CMD_check_main_weekly.yaml actions
  • actions/checkout v2 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
  • r-lib/actions/setup-tinytex v2 composite
.github/workflows/nightly_cleanup_Hades.yml actions
  • c-hive/gha-remove-artifacts v1 composite
DESCRIPTION cran
  • DatabaseConnector >= 5.0.0 depends
  • R >= 3.6.0 depends
  • ParallelLogger >= 3.0.0 imports
  • RJSONIO * imports
  • SqlRender >= 1.7.0 imports
  • bit64 * imports
  • checkmate * imports
  • digest * imports
  • dplyr * imports
  • lubridate * imports
  • readr >= 2.1.0 imports
  • rlang * imports
  • stringi >= 1.7.6 imports
  • CirceR >= 1.1.1 suggests
  • Eunomia * suggests
  • ROhdsiWebApi * suggests
  • knitr * suggests
  • rmarkdown * suggests
  • testthat * suggests