stanscofi and benchscofi

stanscofi and benchscofi: a new standard for drug repurposing by collaborative filtering - Published in JOSS (2024)

https://github.com/recess-eu-project/stanscofi

Science Score: 100.0%

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

✓
CITATION.cff file
Found CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
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DOI references
Found 7 DOI reference(s) in README and JOSS metadata
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Academic publication links
Links to: joss.theoj.org, zenodo.org
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1 of 1 committers (100.0%) from academic institutions
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JOSS paper metadata
Published in Journal of Open Source Software

Keywords

collaborative-filtering drug-repurposing open-science python science-reproducibility

Scientific Fields

Mathematics Computer Science - 84% confidence

Artificial Intelligence and Machine Learning Computer Science - 76% confidence

Last synced: 4 months ago · JSON representation ·

Repository

Package for STANdard drug Screening by COllaborative FIltering. Performs benchmarks against datasets and SotA algorithms, and implements training, validation and testing procedures.

Basic Info

Host: GitHub
Owner: RECeSS-EU-Project
License: mit
Language: Python
Default Branch: master
Homepage: https://recess-eu-project.github.io/stanscofi/
Size: 19.2 MB

Statistics

Stars: 1
Watchers: 1
Forks: 1
Open Issues: 0
Releases: 6

Topics

collaborative-filtering drug-repurposing open-science python science-reproducibility

Created over 2 years ago · Last pushed 10 months ago

Metadata Files

Readme License Citation Codemeta Zenodo

STANdard for drug Screening with COllaborative FIltering (stanscofi) Python Package

This repository is a part of the EU-funded RECeSS project (#101102016), and hosts the code for the open-source Python package stanscofi for the development of collaborative filtering-based drug repurposing algorithms.

GitHub

Statement of need

As of 2022, current drug development pipelines last around 10 years, costing $2billion in average, while drug commercialization failure rates go up to 90%. These issues can be mitigated by drug repurposing, where chemical compounds are screened for new therapeutic indications in a systematic fashion. In prior works, this approach has been implemented through collaborative filtering. This semi-supervised learning framework leverages known drug-disease matchings in order to recommend new ones.

The stanscofi package comprises method-agnostic training, validation, preprocessing and visualization procedures on several published drug repurposing datasets. The proper implementation of these steps is crucial in order to avoid data leakage, i.e., the model is learnt over information that should be unavailable at prediction time. Indeed, data leakage is the source of a major reproducibility crisis in machine learning. This will be avoided by building training and validation sets which are weakly correlated with respect to the drug and disease feature vectors. The main performance metric will be the area under the curve (AUC), which estimates the diagnostic ability of a recommender system better than accuracy in imbalanced datasets.

Medium-term outcomes to this package will significantly alleviate the economic burden of drug discovery pipelines, and will help find treatments in a more sustainable manner, especially for rare or tropical neglected diseases.

For more information about the datasets accessible in stanscofi, please refer to the following repository.

Install the latest release

Run one of the following commands:

```bash

Using pip: install in Python env

pip install stanscofi

Using Anaconda: install in Python env

conda install -c recess stanscofi

Using the Docker image: will open a container

docker push recessproject/stanscofi:2.0.0 ``` Documentation about stanscofi can be found at this page. The complete list of dependencies for stanscofi can be found at requirements.txt (pip) or meta.yaml (conda).

Licence

This repository is under an OSI-approved MIT license.

Citation

If you use stanscofi in academic research, please cite it as follows

@article{reda2024stanscofi, title={stanscofi and benchscofi: a new standard for drug repurposing by collaborative filtering}, author={R{\'e}da, Cl{\'e}mence and Vie, Jill-J{\^e}nn and Wolkenhauer, Olaf}, journal={Journal of Open Source Software}, volume={9}, number={93}, pages={5973}, year={2024} }

Community guidelines with respect to contributions, issue reporting, and support

Pull requests and issue flagging are welcome, and can be made through the GitHub interface. Support can be provided by reaching out to recess-project[at]proton.me. However, please note that contributors and users must abide by the Code of Conduct.

Owner

Name: RECeSS EU project
Login: RECeSS-EU-Project
Kind: user
Location: Rostock, Germany
Company: Universität Rostock

Website: http://recess-eu-project.github.io/
Twitter: recess_eu_proj
Repositories: 1
Profile: https://github.com/RECeSS-EU-Project

The RECeSS (Robust Explainable Controllable Standard for drug Screening) project is funded by a Marie Skłodowska-Curie Postdoctoral Fellowship 2022.

JOSS Publication

stanscofi and benchscofi: a new standard for drug repurposing by collaborative filtering

Published

January 25, 2024

DOI

10.21105/joss.05973

Volume 9, Issue 93, Page 5973

Authors

Clémence Réda

Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, G-18051, Germany

Jill-Jênn Vie

Soda Team, Inria Saclay, F-91120 Palaiseau, France

Olaf Wolkenhauer

Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, G-18051, Germany, Leibniz-Institute for Food Systems Biology, Freising, G-85354, Germany, Stellenbosch Institute of Advanced Study, Wallenberg Research Centre, Stellenbosch, SA-7602, South Africa

Editor

Nikoleta Glynatsi

Citation (CITATION.cff)

cff-version: "1.2.0"
authors:
- family-names: Réda
  given-names: Clémence
  orcid: "https://orcid.org/0000-0003-3238-0258"
- family-names: Vie
  given-names: Jill-Jênn
  orcid: "https://orcid.org/0000-0002-9304-2220"
- family-names: Wolkenhauer
  given-names: Olaf
  orcid: "https://orcid.org/0000-0001-6105-2937"
doi: 10.5281/zenodo.10561760
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Réda
    given-names: Clémence
    orcid: "https://orcid.org/0000-0003-3238-0258"
  - family-names: Vie
    given-names: Jill-Jênn
    orcid: "https://orcid.org/0000-0002-9304-2220"
  - family-names: Wolkenhauer
    given-names: Olaf
    orcid: "https://orcid.org/0000-0001-6105-2937"
  date-published: 2024-01-25
  doi: 10.21105/joss.05973
  issn: 2475-9066
  issue: 93
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 5973
  title: "stanscofi and benchscofi: a new standard for drug repurposing
    by collaborative filtering"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.05973"
  volume: 9
title: "stanscofi and benchscofi: a new standard for drug repurposing by
  collaborative filtering"

CodeMeta (codemeta.json)

{
  "@context": "https://doi.org/10.5063/schema/codemeta-2.0",
  "@type": "SoftwareSourceCode",
  "license": "https://spdx.org/licenses/MIT",
  "codeRepository": "git+https://github.com/RECeSS-EU-Project/stanscofi.git",
  "dateCreated": "2023-06-09",
  "datePublished": "2023-06-10",
  "dateModified": "2023-07-20",
  "downloadUrl": "https://github.com/RECeSS-EU-Project/stanscofi/archive/refs/heads/master.zip",
  "issueTracker": "https://github.com/RECeSS-EU-Project/stanscofi/issues",
  "name": "stanscofi",
  "version": "2.0.0",
  "softwareVersion": "2.0.0",
  "identifier": "10.5281/zenodo.8038847",
  "description": "Package for STANdard drug Screening by COllaborative FIltering. Performs benchmarks against datasets and SotA algorithms, and implements training, validation and testing procedures.",
  "applicationCategory": "Drug development",
  "releaseNotes": "This version passes all automated tests, and is automatically uploaded to Anaconda, PyPI, and Zenodo.",
  "funding": "RECeSS - Robust Explainable Controllable Standard for drug Screening (101102016)",
  "developmentStatus": "active",
  "isPartOf": "https://recess-eu-project.github.io/",
  "readme": "https://github.com/RECeSS-EU-Project/stanscofi/blob/master/README.md",
  "funder": {
    "@type": "Organization",
    "name": "European Union's Horizon 2020 research and innovation programme"
  },
  "keywords": [
    "Python",
    "collaborative filtering",
    "open science",
    "drug repurposing",
    "science reproducibility"
  ],
  "programmingLanguage": [
    "Python 3"
  ],
  "softwareRequirements": [
    "pandas>=1.1.4",
    "numpy>=1.19.4",
    "scikit-learn>=0.24.0",
    "scipy>=1.5.4",
    "matplotlib>=3.3.2",
    "threadpoolctl>=3.1.0",
    "joblib>=1.0.1",
    "tqdm>=4.58.0",
    "codecarbon>=2.2.2",
    "seaborn>=0.11.0"
  ],
  "author": [
    {
      "@type": "Person",
      "@id": "https://orcid.org/0000-0003-3238-0258",
      "givenName": "Clémence",
      "familyName": "Réda",
      "email": "clemence.reda@uni-rostock.de",
      "affiliation": {
        "@type": "Organization",
        "name": "Systems Biology and Informatics, University of Rostock, Rostock, Germany"
      }
    }
  ],
  "maintainer": [
    {
      "@type": "Person",
      "@id": "https://orcid.org/0000-0003-3238-0258",
      "givenName": "Clémence",
      "familyName": "Réda",
      "email": "clemence.reda@uni-rostock.de",
      "affiliation": {
        "@type": "Organization",
        "name": "Systems Biology and Informatics, University of Rostock, Rostock, Germany"
      }
    }
  ]
}

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Total packages: 1
Total downloads:
- pypi 113 last-month

Total dependent packages: 1
Total dependent repositories: 0
Total versions: 6
Total maintainers: 1

pypi.org: stanscofi

Package for STANdard drug Screening by COllaborative FIltering. Performs benchmarks against datasets and SotA algorithms, and implements training, validation and testing procedures.

Homepage: https://github.com/RECeSS-EU-Project/stanscofi
Documentation: https://stanscofi.readthedocs.io/
License: MIT License
Latest release: 2.0.1
published almost 2 years ago

Versions: 6
Dependent Packages: 1
Dependent Repositories: 0
Downloads: 113 Last month

Rankings

Dependent packages count: 7.3%

Downloads: 15.6%

Average: 26.8%

Forks count: 30.4%

Stargazers count: 39.3%

Dependent repos count: 41.5%

Maintainers (1)

recess

Last synced: 4 months ago

Dependencies

.github/workflows/draft-paper.yml actions

actions/checkout v3 composite
actions/upload-artifact v1 composite
openjournals/openjournals-draft-action master composite

.github/workflows/gh-pages.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite
peaceiris/actions-gh-pages v3 composite

.github/workflows/post-push-test.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite
codecov/codecov-action v3 composite

pip/requirements.txt pypi

codecarbon >=2.2.2
cute-ranking >=0.0.3
fastcluster >=1.2.6
joblib >=1.0.1
matplotlib >=3.3.2
numpy >=1.19.4
pandas >=1.1.4
scikit-learn >=1.2.2
scipy >=1.5.4
seaborn >=0.11.0
threadpoolctl >=3.1.0
tqdm >=4.58.0
umap-learn >=0.5.3

pyproject.toml pypi

setup.py pypi

codecarbon >=2.2.2
cute-ranking >=0.0.3
fastcluster >=1.2.6
joblib >=1.0.1
matplotlib >=3.3.2
numpy >=1.19.4
pandas >=1.1.4
scikit-learn >=1.2.2
scipy >=1.5.4
seaborn >=0.11.0
threadpoolctl >=3.1.0
tqdm >=4.58.0
umap-learn >=0.5.3

.github/workflows/conda-release.yml actions

actions/checkout v2.3.5 composite
s-weigand/setup-conda v1 composite

.github/workflows/pip-release.yml actions

actions/checkout v2 composite
actions/setup-python v1 composite

Dockerfile docker

python 3.8.18-bullseye build

stanscofi and benchscofi

Science Score: 100.0%

Keywords

Scientific Fields

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

STANdard for drug Screening with COllaborative FIltering (stanscofi) Python Package

Statement of need

Install the latest release

Using pip: install in Python env

Using Anaconda: install in Python env

Using the Docker image: will open a container

Licence

Citation

Community guidelines with respect to contributions, issue reporting, and support

Owner

JOSS Publication

stanscofi and benchscofi: a new standard for drug repurposing by collaborative filtering

Authors

Editor

Tags

Citation (CITATION.cff)

CodeMeta (codemeta.json)

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

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Issue Labels

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pypi.org: stanscofi

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Maintainers (1)

Dependencies