Metadata-Version: 2.5
Name: aabatlas
Version: 0.1.0
Summary: Client for the antibodyome-atlas, a curated catalog of autoantibody profiling datasets and papers
Project-URL: Homepage, https://github.com/ahcm088/antibodyome-atlas
Project-URL: Issues, https://github.com/ahcm088/antibodyome-atlas/issues
Author-email: Alexandre Marques <marquesufcg@gmail.com>
License: MIT
License-File: LICENSE
Keywords: ArrayExpress,GEO,autoantibody,bioinformatics,proteomics
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.9
Requires-Dist: pandas>=1.5
Requires-Dist: requests>=2.31
Provides-Extra: test
Requires-Dist: pytest>=7.0; extra == 'test'
Description-Content-Type: text/markdown

# aabatlas

Python client for the [antibodyome-atlas](https://github.com/ahcm088/antibodyome-atlas), a curated catalog of autoantibody profiling datasets and papers. See `schema/README.md` in the atlas repo for the data model. Mirrors the R client, [AAbAtlas](../r-package).

## Install

Not yet on PyPI. Until then, install from GitHub:

```bash
pip install "git+https://github.com/ahcm088/antibodyome-atlas.git#subdirectory=python-package"
```

## Usage

```python
import aabatlas

# browse
ds = aabatlas.list_datasets()
ds[(ds["record_type"] == "DATASET") & (ds["total_sample_n"] > 100)][["atlas_id", "title", "total_sample_n"]]

# one record, with its publication and platforms resolved
rec = aabatlas.get_dataset("AAB-000004")
rec["title"]
rec["publication"]["citation"]

# citation ready to paste into a manuscript
aabatlas.get_citation("AAB-000004")

# download the underlying file
aabatlas.download("AAB-000004")
```

By default every function reads the latest curated data (`ref="main"`). Pin a release tag for reproducibility in a publication:

```python
aabatlas.list_datasets(ref="v1.0.0")
```
