| Name | copairs JSON |
| Version |
0.5.0
JSON |
| download |
| home_page | None |
| Summary | Find pairs and compute metrics between them |
| upload_time | 2025-02-21 17:09:53 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | None |
| keywords |
pairwise
replication
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# copairs
`copairs` is a Python package for finding groups of profiles based on metadata and calculate mean Average Precision to assess intra- vs inter-group similarities.
## Getting started
### System requirements
copairs supports Python 3.8+ and should work with all modern operating systems (tested with MacOS 13.5, Ubuntu 18.04, Windows 10).
### Dependencies
copairs depends on widely used Python packages:
* numpy
* pandas
* tqdm
* statsmodels
* [optional] plotly
### Installation
To install copairs and dependencies, run:
```bash
pip install copairs
```
To also install dependencies for running examples, run:
```bash
pip install copairs[demo]
```
### Testing
To run tests, run:
```bash
pip install -e .[test]
pytest
```
## Usage
We provide examples demonstrating how to use copairs for:
- [grouping profiles based on their metadata](./examples/finding_pairs.ipynb)
- [calculating mAP to assess phenotypic activity of perturbations](./examples/phenotypic_activity.ipynb)
- [calculating mAP to assess phenotypic consistency of perturbations](./examples/phenotypic_consistency.ipynb)
- [estimating null size for mAP p-value calculation](./examples/null_size.ipynb)
## Citation
If you find this work useful for your research, please cite our [pre-print](https://doi.org/10.1101/2024.04.01.587631):
Kalinin, A.A., Arevalo, J., Vulliard, L., Serrano, E., Tsang, H., Bornholdt, M., Rajwa, B., Carpenter, A.E., Way, G.P. and Singh, S., 2024. A versatile information retrieval framework for evaluating profile strength and similarity. bioRxiv, pp.2024-04. doi:10.1101/2024.04.01.587631
BibTeX:
```
@article{kalinin2024versatile,
title={A versatile information retrieval framework for evaluating profile strength and similarity},
author={Kalinin, Alexandr A and Arevalo, John and Vulliard, Loan and Serrano, Erik and Tsang, Hillary and Bornholdt, Michael and Rajwa, Bartek and Carpenter, Anne E and Way, Gregory P and Singh, Shantanu},
journal={bioRxiv},
pages={2024--04},
year={2024},
doi={10.1101/2024.04.01.587631}
}
```
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