Metadata-Version: 2.4
Name: plotly_for_scanpy
Version: 0.1.0
Summary: Plotly-based visualization tools for Scanpy data
Author-email: Klim Kostiuk <2601074@gmail.com>
License: MIT License
        
        Copyright (c) 2024 Klim Kostiuk
        
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Project-URL: Homepage, https://github.com/yourusername/plotly_for_scanpy
Project-URL: Bug Tracker, https://github.com/yourusername/plotly_for_scanpy/issues
Project-URL: Documentation, https://colab.research.google.com/drive/1pHt8m-wIVS2B7aUbjrlsNrNWV2JsEI-E
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: plotly>=5.0.0
Requires-Dist: dash
Requires-Dist: scipy
Requires-Dist: anndata
Requires-Dist: webcolors
Dynamic: license-file

# plotly_for_scanpy

Interactive Plotly-based visualization tools for Scanpy single-cell data analysis, providing drop-in alternatives to scanpy.pl functions with enhanced interactivity.

## Installation

```bash
pip install plotly_for_scanpy
```

## Features

- **Dynamic Downsampling**: Efficiently visualize large datasets with intelligent point reduction
- **Interactive Plots**: All visualizations are fully interactive with zoom, pan, and hover functionality
- **Scanpy Integration**: Works seamlessly with AnnData objects
- **Publication Quality**: Easily export to HTML or static formats

## Example Usage

```python
import scanpy as sc
import plotly_for_scanpy as psc

# Load data
adata = sc.datasets.pbmc3k()
sc.pp.normalize_total(adata)
sc.pp.log1p(adata)
sc.pp.highly_variable_genes(adata)
sc.pp.pca(adata)
sc.pp.neighbors(adata)
sc.tl.umap(adata)
sc.tl.leiden(adata)

# Use interactive UMAP visualization
psc.umap(adata, color=['leiden'])

# Visualize with dynamic downsampling for large datasets
fig = psc.umap(adata, color='leiden', return_fig=True)
dynamic_fig = psc.dd(fig, resolution=10000)
dynamic_fig.show()
```

## Documentation

Full examples and tutorials:
- [Interactive Colab Demo](https://colab.research.google.com/drive/1pHt8m-wIVS2B7aUbjrlsNrNWV2JsEI-E)

## License

MIT License
