biotmle
Bioc currentTargeted Learning with Moderated Statistics for Biomarker Discovery
Release Lineage
Entered 3.5 · Apr 25, 2017
Current · Requires R 4.6
Description
Tools for differential expression biomarker discovery based on microarray and next-generation sequencing data that leverage efficient semiparametric estimators of the average treatment effect for variable importance analysis. Estimation and inference of the (marginal) average treatment effects of potential biomarkers are computed by targeted minimum loss-based estimation, with joint, stable inference constructed across all biomarkers using a generalization of moderated statistics for use with the estimated efficient influence function. The procedure accommodates the use of ensemble machine learning for the estimation of nuisance functions.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
10 7 exported
Complexity
2.9 avg / 9 max
Call network
10 nodes / 1 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
1,633
Files
80
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
8
Internal functions
3
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.21
testthat edition
–
CI present
Yes
CI type
["github-actions"]
PR gated
Yes
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
7.1%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.0
System requirements
–
C++ standard
–
License
MIT + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
19
First release
2017-09-07
Latest release
2026-04-28
Avg cadence
181 days
Cold removal rate
–
Dep drift
22
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 50%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Topics
People
- Nima Hejazi author maintainer cph
- Philippe Boileau contributor
- Weixin Cai contributor
- Alan Hubbard author ths
- Mark van der Laan author ths