Science Score: 67.0%
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✓codemeta.json file
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✓.zenodo.json file
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✓DOI references
Found 5 DOI reference(s) in README -
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Links to: zenodo.org -
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (14.2%) to scientific vocabulary
Keywords
Repository
Generate Dose-Response Curves in Python
Basic Info
- Host: GitHub
- Owner: tlint101
- License: gpl-3.0
- Language: Jupyter Notebook
- Default Branch: main
- Homepage: https://py50.readthedocs.io/en/latest/
- Size: 10.4 MB
Statistics
- Stars: 9
- Watchers: 3
- Forks: 4
- Open Issues: 0
- Releases: 18
Topics
Metadata Files
README.md
py50: Generate Dose-Response Curves
Summary
The aim of py50 is to make the generation of dose-response curves and annotated plots with statistics. The project was created primarily for my personal use and for my coworkers/classmates. I found many of my classmates/coworkers were using a program that I find to be unfriendly in generating dose-response curves or with calculating statistics and plots. During my search, I found other helpful repositories that can generate dose-response curves, calculate statistics, or make annotated plots. However, I found that these packages did not meet my requirements:
- Use Pandas for the Data so that it can be easily plugged into a Jupyter Notebook or Python scripts
- Adaptable to user needs
- Easy to use (hopefully!)
The dose-response curves in py50 are built using the four parameter logistic regression model:
$Y = \text{Min} + \frac{\text{Max} - \text{Min}}{1 + \left(\frac{X}{\text{IC50}}\right)^{\text{Hill coefficient}}}$
where min is the minimum response value, max is the maximum response value, Y is the response values of the curves, and X is the concentration.
The statistics and annotated plots are wrapped from Pingouin and Statannotations. This may have been done inelegantly and will be updated based on my use or recommendations by others. As things stand, this project meets my needs and the needs of my classmates/coworkers. Hopefully it can meet the needs of others.
Installation
pip install py50
Pacakge can be upgraded specifically using pip with the following:
pip install py50 -U
Tutorial
Documentation can be found here.
A Jupyter Notebook demoing the code can be found here.
A blog post demoing the code can be found at Practice in Code
Web Application 
For those who are not versed in python coding, py50 has been converted into a web application using Streamlit!
The web application can be found here: py50-app
The repository for the Streamlit app version can be found here: py50-streamlit
NOTE: Updates to the web application take more time. Updates will be made when possible or upon request.
Future Work
With the release of py50 v1.0.0, I have finished a project that has been on my mind for the past six months. My aim now will be to reformat the code for maintainability and to fix any bugs that I find or others report. I plan on maintaining py50 for the foreseeable future. As such, my current "To-Do" list (in no particular order) are as follows:
- [ ] Complete To-Do notes in Python script
- [X] Update Tutorials for clarity
- [X] Update py50 Streamlit to version 1.0.0
- [ ] Refactor code for maintainability
- [ ] Add error messages!
- Provide KNIME workflow?
Citation
If you are interested in citing the repository, the BibTeX reference is as follows:
aiignore
@software{lin_2024_14523624,
author = {Lin, Tony Eight},
title = {py50: Generate Dose-Response Curves},
month = dec,
year = 2024,
publisher = {Zenodo},
version = {v1.0.10},
doi = {10.5281/zenodo.14523624},
url = {https://doi.org/10.5281/zenodo.14523624},
}
All versions can be linked to the Zenodo repository here:
Thanks for your interest!
Owner
- Name: T Lint
- Login: tlint101
- Kind: user
- Repositories: 1
- Profile: https://github.com/tlint101
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: 'py50: Generate Dose-Response Curves'
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Tony Eight
family-names: Lin
email: tonyelin@tmu.edu.tw
repository-code: 'https://github.com/tlint101/py50.git'
url: 'https://py50.readthedocs.io/en/latest/'
license: GPL-3.0
version: 1.0.10
date-released: '2024-12-19'
GitHub Events
Total
- Release event: 3
- Watch event: 2
- Push event: 11
- Create event: 2
Last Year
- Release event: 3
- Watch event: 2
- Push event: 11
- Create event: 2
Issues and Pull Requests
Last synced: over 1 year ago
All Time
- Total issues: 1
- Total pull requests: 0
- Average time to close issues: about 2 hours
- Average time to close pull requests: N/A
- Total issue authors: 1
- Total pull request authors: 0
- Average comments per issue: 3.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 0
- Average time to close issues: about 2 hours
- Average time to close pull requests: N/A
- Issue authors: 1
- Pull request authors: 0
- Average comments per issue: 3.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- nabilr (1)
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- pypi 112 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 39
- Total maintainers: 1
pypi.org: py50
Generate Dose-Response Curves
- Documentation: https://py50.readthedocs.io/en/latest/
- License: GPL-3.0-only
-
Latest release: 1.0.10
published about 1 year ago
Rankings
Maintainers (1)
Dependencies
- numpy 1.26.2
- pandas 2.1.3
- python-dateutil 2.8.2
- pytz 2023.3.post1
- scipy 1.11.3
- six 1.16.0
- tzdata 2023.3
- matplotlib >=3.8.1
- numpy >=1.26.2
- pandas >=2.1.3
- python ^3.9,<3.13
- scipy >=1.11.3