Metadata-Version: 2.1
Name: cycleenrichr
Version: 0.0.8
Summary: Cycleenrichr uses PrismEXP predictions to calculate enrichment of gene sets that do not have gene annotations.
Home-page: https://github.com/maayanlab/cycleenrichr
Author: Alexander Lachmann
Author-email: alexander.lachmann@mssm.edu
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE.md

### Cycle Enrichr

Enrichment of gene sets with no gene annotations leveraging ARCHS4 and PrismExp gene function prediction.


## Usage

#### Installation
```
pip3 install cycleenrichr
```
#### Download Prediction File
```python
# download precomputed predictions file from PrismExp

import cycleenrichr as cycle
cycle.load.download("predictions.h5")
```

### Run Set Enrichment for Gene Set Library

```python
import cycleenrichr as cycle

# load gene set libary from Enrichr
library = cycle.enrichr.get_library("KEGG_2021_Human")

predictions_path = "predictions.h5"

result = cycle.enrichment.enrich(library, predictions_path)
```
