Metadata-Version: 2.1
Name: scquill
Version: 0.2.1
Summary: Approximate any single cell data set, saving >99% of memory and runtime.
License: MIT
Author: Fabio Zanini
Author-email: fabio.zanini@unsw.edu.au
Requires-Python: >=3.11,<3.13
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: h5py (>=3.10.0,<4.0.0)
Requires-Dist: hdf5plugin (>=4.2.0,<5.0.0)
Requires-Dist: pyyaml (>=6.0.1,<7.0.0)
Requires-Dist: scanpy (>=1.9.6,<2.0.0)
Description-Content-Type: text/markdown

<img src="https://raw.githubusercontent.com/fabilab/scquill/main/logo.png" width="150" height="150">

# scquill
Approximate any single cell data set, saving >99% of memory and runtime.


## Approximating a single cell data set
```python
import scquill

q = Quill(
    filename='myscdata.h5ad',
    output_filename='myapprox.h5',
    celltype_column="cell_annotation",
)

q()
```

**Steps:**
- Load dataset if necessary
- Preprocess
- Compress
- Store to output file
- (TODO): Provide an interface to explore approximations.

## Authors
Fabio Zanini @[fabilab](https://fabilab.org)

