Package 'clinTrialData'

Description

Returns the path to the local cache directory where downloaded clinical trial datasets are stored. The location follows the platform-specific user data directory convention via tools::R_user_dir().

You can delete any subdirectory here to remove a cached dataset, or clear the entire directory to free disk space.

Usage

cache_dir()

Value

A character string with the path to the cache directory.

Examples

cache_dir()

Description

The clinTrialData package contains clinical trial datasets from multiple sources, stored in Parquet format. Data is accessed using connector functions.

Available Data Sources

CDISC Pilot 01 Study

The CDISC Pilot 01 study data includes both ADaM and SDTM domains.

ADaM datasets include:

• ADSL: Subject-Level Analysis Dataset

• ADAE: Adverse Events Analysis Dataset

• ADLBC: Laboratory Analysis Dataset (Chemistry)

• ADLBH: Laboratory Analysis Dataset (Hematology)

• ADLBHY: Laboratory Analysis Dataset (Hy's Law)

• ADQSADAS: ADAS-Cog Questionnaire Analysis Dataset

• ADQSCIBC: CIBC Questionnaire Analysis Dataset

• ADQSNPIX: NPI-X Questionnaire Analysis Dataset

• ADTTE: Time-to-Event Analysis Dataset

• ADVS: Vital Signs Analysis Dataset

SDTM datasets include:

• DM: Demographics

• AE: Adverse Events

• VS: Vital Signs

• LB: Laboratory Test Results

• And 18 additional domains (see list_data_sources() for details)

Usage

Data sources are discovered by scanning the package directory structure. List available datasets with list_data_sources().

Access data using the connection function:

# Connect to any data source (e.g., CDISC Pilot data)
db <- connect_clinical_data("cdisc_pilot")

# List available datasets
db$adam$list_content_cnt()

# Read a dataset
adsl <- db$adam$read_cnt("adsl")

# See all available data sources
list_data_sources()

Data Format

Datasets are stored in Parquet format:

• Columnar storage

• Fast reads

• Compression

• Cross-platform compatibility

Source

CDISC Pilot 01 Study Data Various clinical trial data sources

References

CDISC. Clinical Data Interchange Standards Consortium. https://www.cdisc.org/

Description

Generic connection function that allows access to any data source in the package. Data sources are automatically discovered by scanning the package's example data directory structure.

Usage

connect_clinical_data(source = "cdisc_pilot")

Arguments

Value

A connectors object

Examples

if (interactive()) {
  # Connect to CDISC Pilot data
  db <- connect_clinical_data("cdisc_pilot")

  # List available datasets
  db$adam$list_content_cnt()

  # Read a dataset (requires the arrow package)
  if (requireNamespace("arrow", quietly = TRUE)) {
    adsl <- db$adam$read_cnt("adsl")
  }

  # List available sources
  list_data_sources()
}

Description

Fetches and displays metadata for any study available in the clinTrialData library – without downloading the full dataset. Metadata includes the study description, available domains and datasets, subject count, version, and data source attribution.

For studies already downloaded via download_study(), the metadata is read from the local cache and works offline. For studies not yet downloaded, a small JSON file (~2KB) is fetched from the GitHub Release.

Usage

dataset_info(source, repo = "Lovemore-Gakava/clinTrialData")

Arguments

Value

Invisibly returns the metadata as a named list.

Examples

dataset_info("cdisc_pilot")

Description

Downloads a study dataset from a GitHub Release and stores it in the local cache (see cache_dir()). Once downloaded, the study is available to connect_clinical_data() without an internet connection.

Requires the piggyback package.

Usage

download_study(
  source,
  version = "latest",
  force = FALSE,
  repo = "Lovemore-Gakava/clinTrialData"
)

Arguments

Value

Invisibly returns the path to the cached study directory.

Examples

if (interactive()) {
  # Download a study not bundled with the package
  download_study("cdisc_pilot_extended")

  # Then connect as usual
  db <- connect_clinical_data("cdisc_pilot_extended")
}

Description

Returns a data frame of all clinical trial studies available as GitHub Release assets, along with their local cache status. Studies marked as cached = TRUE are already downloaded and available for use with connect_clinical_data() without an internet connection.

When GitHub is unreachable, the function falls back to the last successfully fetched listing (if available) and issues a warning. The cached column is always recomputed from the local filesystem.

Requires the piggyback package.

Usage

list_available_studies(repo = "Lovemore-Gakava/clinTrialData")

Arguments

Value

A data frame with columns:

source

Study name (pass this to download_study() or connect_clinical_data())

version

Release tag the asset belongs to

size_mb

Asset size in megabytes

cached

TRUE if the study is already in the local cache

Examples

if (interactive()) {
  list_available_studies()
}

Description

Returns information about all clinical datasets available locally – both datasets bundled with the package and any datasets previously downloaded via download_study(). The location column indicates whether a dataset is "bundled" (shipped with the package) or "cached" (downloaded to the user cache directory).

To see datasets available for download from GitHub, use list_available_studies().

Usage

list_data_sources()

Value

A data frame with columns:

source

Dataset name (pass to connect_clinical_data())

description

Human-readable study description

domains

Comma-separated list of available data domains (e.g. "adam, sdtm")

format

Storage format ("parquet")

location

Either "bundled" or "cached"

Examples

list_data_sources()

Description

S3 method for remove_cnt that checks if the study folder is locked before allowing remove operations.

Usage

## S3 method for class 'ConnectorLockedFS'
remove_cnt(connector_object, name, ...)

Arguments

Value

Invisible connector_object

Description

S3 method for write_cnt that checks if the study folder is locked before allowing write operations.

Usage

## S3 method for class 'ConnectorLockedFS'
write_cnt(connector_object, x, name, overwrite = FALSE, ...)

Arguments

Value

Invisible connector_object