Metadata-Version: 2.1
Name: cPredictor
Version: 0.1.2
Summary: Cell command line predictor
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: setuptools (<=57.5.0)
Requires-Dist: wheel
Requires-Dist: python-build
Requires-Dist: pytest-cov
Requires-Dist: h5py
Requires-Dist: numpy (<1.24,>=1.23.3)
Requires-Dist: pandas (>=1.4.4)
Requires-Dist: scikit-learn
Requires-Dist: scanpy (>=1.9.1)
Requires-Dist: importlib-resources

[![PyPI version](https://badge.fury.io/py/cPredictor.svg)](https://badge.fury.io/py/cPredictor)
[![CI/CD](https://github.com/Arts-of-coding/cPredictor/actions/workflows/ci-cd.yml/badge.svg)](https://github.com/Arts-of-coding/cPredictor/actions/workflows/ci-cd.yml)
[![Maintainability](https://api.codeclimate.com/v1/badges/598ba117b586183c46a8/maintainability)](https://codeclimate.com/github/Arts-of-coding/cPredictor/maintainability)
[![Test Coverage](https://api.codeclimate.com/v1/badges/598ba117b586183c46a8/test_coverage)](https://codeclimate.com/github/Arts-of-coding/cPredictor/test_coverage)
# cma
This repository defines a command-line tool to predict (cPredictor) datasets according to a cell meta-atlases. At the present time only the meta-atlas for the cornea has been implemented.


Install cPredictor into a conda environment and install with PyPI:
```
$ conda create -n cPredictor python=3.9 pip
$ conda activate cPredictor
$ pip install cPredictor
```
To see what each of the current functions do you can run these commands:
```
$ SVM_performance --help
$ SVM_prediction --help
$ SVM_import --help
$ SVM_pseudobulk --help
```
The documentation will be extended and improved upon in later versions.
