Package: lineager 0.1.1.9000

Ndoh Penn

lineager: Row-Level Data Provenance and Exclusion Tracking

Provides row-level data provenance tracking for analytical pipelines. Tags datasets with unique lineage identifiers that persist through filter, join, and derive operations. Requires documented reasons for every row exclusion, capturing who was removed, why, and at which pipeline stage. Variable derivations are registered as structured specifications linking output variables back to their source. Any row in any downstream dataset can be traced back to its origin via lg_trace(). Generates structured HTML provenance reports suitable for regulatory submissions, internal audit, or analytical documentation. General-purpose: works for clinical data, machine learning pipelines, financial modelling, epidemiology, or any workflow where row-level accountability matters. Optional features support pharmaceutical users including population flag definitions, source-to-analysis variable mapping, and Reviewer's Guide-aligned report output. Complements the 'regulog' package for tamper-evident session-level audit logging. For more details see <https://reprostats.org/lineager/>.

Authors:Ndoh Penn [aut, cre]

lineager_0.1.1.9000.tar.gz
lineager_0.1.1.9000.zip(r-4.7-any)lineager_0.1.1.9000.zip(r-4.6-any)lineager_0.1.1.9000.zip(r-4.5-any)
lineager_0.1.1.9000.tgz(r-4.6-any)lineager_0.1.1.9000.tgz(r-4.5-any)
lineager_0.1.1.9000.tar.gz(r-4.7-any)lineager_0.1.1.9000.tar.gz(r-4.6-any)
lineager_0.1.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
lineager/json (API)

# Install 'lineager' in R:
install.packages('lineager', repos = c('https://repro-stats.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/repro-stats/lineager/issues

On CRAN:

Conda:

adamaudit-trailcdiscclinical-trialsdata-provenancepharmareproducibilitysdtm

5.38 score 2 stars 305 downloads 18 exports 15 dependencies

Last updated from:3dbf8053e5. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK179
source / vignettesOK363
linux-releaseOK165
macos-releaseOK85
macos-oldrelOK119
windows-develOK91
windows-releaseOK70
windows-oldrelOK71
wasm-releaseOK113

Exports:%>%lg_derivelg_dispositionlg_endlg_exclusionslg_filterlg_historylg_idlg_joinlg_lineagelg_operationslg_plotlg_populationlg_reportlg_speclg_startlg_taglg_trace

Dependencies:clidplyrgenericsgluelifecyclemagrittrpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithr

Getting started with lineager
1. Start a session | 2. Tag your source datasets | Tagging multiple datasets | 3. Derive new variables | 4. Join datasets with lineage tracking | 5. Filter with mandatory exclusion reasons | 6. The session operation log | 7. End the session | 8. Complete minimal workflow | 9. Visualise the pipeline
Rendered fromgetting-started.Rmdusingknitr::rmarkdown

Last update: 2026-07-30
Started: 2026-06-24

Populations, variable specifications, and reporting
Setup: a complete pipeline | Derive analysis variables | 1. lg_population(): documenting analysis sets | Multiple populations | What lg_population() records | print method | 2. lg_spec(): documenting variable derivations | Documenting flag derivations | Overwriting a spec | 3. lg_report(): generating the provenance report | In-memory report (inspect without writing to disk) | Write to file | Report arguments | 4. A note on CDISC-specific usage | 5. Visualise the pipeline lineage | 6. End the session
Rendered frompopulations-and-reporting.Rmdusingknitr::rmarkdown

Last update: 2026-07-20
Started: 2026-06-24

Exclusion tracking and subject tracing
Setup: a realistic multi-stage pipeline | 1. lg_filter() in depth | Mandatory reason | reason_code: machine-readable classification | population: grouping exclusions by analysis set | 2. The exclusion registry | Filter by population | Filter by dataset | The exclusion record structure | 3. Disposition tables | Group by reason | Group by population | Group by dataset | 4. Subject tracing | Tracing an excluded subject | Tracing an included subject | Tracing a subject not found | Using the trace result programmatically | 5. The operation log | 6. Visualise exclusions as a lineage graph | 7. Common patterns | Cascaded filters with verbose tracking
Rendered fromexclusion-tracking.Rmdusingknitr::rmarkdown

Last update: 2026-07-08
Started: 2026-06-24