TMLE.jl

TMLE.jl: Targeted Minimum Loss-Based Estimation in Julia - Published in JOSS (2025)

https://github.com/targene/tmle.jl

Science Score: 98.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
Found CITATION.cff file
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codemeta.json file
Found codemeta.json file
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.zenodo.json file
Found .zenodo.json file
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DOI references
Found 12 DOI reference(s) in README and JOSS metadata
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Academic publication links
Links to: springer.com, joss.theoj.org, zenodo.org
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Academic email domains
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Institutional organization owner
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JOSS paper metadata
Published in Journal of Open Source Software

Keywords

causal-inference double-robust julia machine-learning non-parametric-statistics statistics targeted-learning tmle

Last synced: 6 months ago · JSON representation ·

Repository

A Julia implementation of the Targeted Minimum Loss-based Estimation

Basic Info

Host: GitHub
Owner: TARGENE
License: mit
Language: Julia
Default Branch: main
Homepage: https://targene.github.io/TMLE.jl/stable/
Size: 11.4 MB

Statistics

Stars: 21
Watchers: 3
Forks: 5
Open Issues: 22
Releases: 50

Topics

causal-inference double-robust julia machine-learning non-parametric-statistics statistics targeted-learning tmle

Created over 4 years ago · Last pushed 6 months ago

Metadata Files

Readme License Citation

TMLE

GitHub Workflow Status (with branch) Codecov GitHub release (latest SemVer)

Causal inference is essential for understanding the effect of interventions in real-world settings, such as determining whether a treatment improves health outcomes or whether a gene variant contributes to disease risk. Traditional statistical methods, such as linear regression or propensity score matching, often rely on strong modeling assumptions and may fail to provide valid inference when these assumptions are violated—particularly in the presence of high-dimensional data or model misspecification.

TMLE.jl is a Julia package that implements Targeted Maximum Likelihood Estimation (TMLE), a general framework for causal effect estimation that combines machine learning with principles from semiparametric statistics. TMLE provides doubly robust, efficient, and flexible estimation of causal parameters in observational and experimental studies.

Installation

TMLE.jl can be installed via the Package Manager and supports Julia v1.10 and greater.

Pkg Pkg> add TMLE

Documentation

For more information, please visit the documentation

Citation

If you use TMLE.jl for your own work and would like to cite us, here are the BibTeX and APA formats:

BibTeX

bibtex @article{Labayle_TMLE_jl_Targeted_Minimum_2025, author = {Labayle, Olivier and Ponting, Chris P. and van der Laan, Mark J. and Khamseh, Ava and Beentjes, Sjoerd Viktor}, doi = {10.21105/joss.08446}, journal = {Journal of Open Source Software}, month = aug, number = {112}, pages = {8446}, title = {{TMLE.jl: Targeted Minimum Loss-Based Estimation in Julia}}, url = {https://joss.theoj.org/papers/10.21105/joss.08446}, volume = {10}, year = {2025} }

Labayle, O., Ponting, C. P., van der Laan, M. J., Khamseh, A., & Beentjes, S. V. (2025). TMLE.jl: Targeted Minimum Loss-Based Estimation in Julia. Journal of Open Source Software, 10(112), 8446. https://doi.org/10.21105/joss.08446

Contact

A bug, a question or want to say hello? Please fill an issue.

Owner

Name: TarGene
Login: TARGENE
Kind: organization

Repositories: 4
Profile: https://github.com/TARGENE

Targeted Estimation of Genetic Effects

JOSS Publication

TMLE.jl: Targeted Minimum Loss-Based Estimation in Julia

Published

August 18, 2025

DOI

10.21105/joss.08446

Volume 10, Issue 112, Page 8446

Authors

Olivier Labayle

Institute for Regeneration and Repair, University of Edinburgh, Edinburgh EH16 4UU, United Kingdom

Chris P. Ponting

MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom.

Mark J. van der Laan
Division of Biostatistics, University of California, Berkeley, CA, USA

Ava Khamseh

MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom., School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, United Kingdom, Division of Biostatistics, University of California, Berkeley, CA, USA

Sjoerd Viktor Beentjes

MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom., School of Mathematics and Maxwell Institute for Mathematical Sciences, University of Edinburgh, Edinburgh EH9 3FD, United Kingdom, Division of Biostatistics, University of California, Berkeley, CA, USA

Editor

Mehmet Hakan Satman

Citation (CITATION.cff)

cff-version: "1.2.0"
authors:
- family-names: Labayle
  given-names: Olivier
  orcid: "https://orcid.org/0000-0002-3708-3706"
- family-names: Ponting
  given-names: Chris P.
  orcid: "https://orcid.org/0000-0003-0202-7816"
- family-names: Laan
  given-names: Mark J.
  name-particle: van der
- family-names: Khamseh
  given-names: Ava
  orcid: "https://orcid.org/0000-0001-5203-2205"
- family-names: Beentjes
  given-names: Sjoerd Viktor
  orcid: "https://orcid.org/0000-0002-7998-4262"
doi: 10.5281/zenodo.16884264
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Labayle
    given-names: Olivier
    orcid: "https://orcid.org/0000-0002-3708-3706"
  - family-names: Ponting
    given-names: Chris P.
    orcid: "https://orcid.org/0000-0003-0202-7816"
  - family-names: Laan
    given-names: Mark J.
    name-particle: van der
  - family-names: Khamseh
    given-names: Ava
    orcid: "https://orcid.org/0000-0001-5203-2205"
  - family-names: Beentjes
    given-names: Sjoerd Viktor
    orcid: "https://orcid.org/0000-0002-7998-4262"
  date-published: 2025-08-18
  doi: 10.21105/joss.08446
  issn: 2475-9066
  issue: 112
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 8446
  title: "TMLE.jl: Targeted Minimum Loss-Based Estimation in Julia"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.08446"
  volume: 10
title: "TMLE.jl: Targeted Minimum Loss-Based Estimation in Julia"

GitHub Events

Total

Fork event: 1
Create event: 17
Commit comment event: 17
Release event: 5
Issues event: 18
Watch event: 5
Delete event: 2
Member event: 2
Issue comment event: 36
Push event: 181
Pull request review comment event: 19
Pull request event: 18
Pull request review event: 21

Last Year

Fork event: 1
Create event: 17
Commit comment event: 17
Release event: 5
Issues event: 18
Watch event: 5
Delete event: 2
Member event: 2
Issue comment event: 36
Push event: 181
Pull request review comment event: 19
Pull request event: 18
Pull request review event: 21

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 79
Total pull requests: 60
Average time to close issues: 4 months
Average time to close pull requests: 13 days
Total issue authors: 5
Total pull request authors: 7
Average comments per issue: 0.67
Average comments per pull request: 1.07
Merged pull requests: 44
Bot issues: 0
Bot pull requests: 7

Past Year

Issues: 14
Pull requests: 15
Average time to close issues: 11 days
Average time to close pull requests: 8 days
Issue authors: 3
Pull request authors: 5
Average comments per issue: 0.07
Average comments per pull request: 1.73
Merged pull requests: 11
Bot issues: 0
Bot pull requests: 0

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Top Authors

Issue Authors

olivierlabayle (75)
salbalkus (1)
JuliaTagBot (1)
svilupp (1)
joshua-slaughter (1)

Pull Request Authors

olivierlabayle (46)
github-actions[bot] (7)
joshua-slaughter (2)
gdalle (2)
salbalkus (1)
jbytecode (1)
Asantewaah (1)

Top Labels

Issue Labels

enhancement (30) question (12) documentation (6) bug (2) help wanted (1)

Pull Request Labels

Packages

Total packages: 1
Total downloads:
- julia 4 total

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 47

juliahub.com: TMLE