https://github.com/incatools/pandasaurus_cxg
Ontology enrichment tool for CxG standard AnnData files
https://github.com/incatools/pandasaurus_cxg
Last synced: 3 months ago
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Ontology enrichment tool for CxG standard AnnData files
- Host: GitHub
- URL: https://github.com/incatools/pandasaurus_cxg
- Owner: INCATools
- License: apache-2.0
- Created: 2023-04-20T16:37:39.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2025-08-19T09:06:09.000Z (10 months ago)
- Last Synced: 2025-08-19T11:21:41.376Z (10 months ago)
- Language: Jupyter Notebook
- Size: 4.27 MB
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Roadmap: ROADMAP.md
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README
# pandasaurus_cxg
STATUS: early Beta
A library for retrieving and leveraging the semantic context of ontology annotation in [CxG standard](https://github.com/chanzuckerberg/single-cell-curation/blob/main/schema/3.0.0/schema.md) [AnnData files](https://anndata.readthedocs.io/en/latest/).
Slide summarising intended functionality
## Installation
Available on [PyPi](https://pypi.org/project/pandasaurus-cxg)
$ pip3 install pandasaurus_cxg
#### Detailed installation guide for pygraphviz issue
During package installation, sometimes the pygraphviz package installation is failing on **macOS** due to Graphviz may be
installed in a location that is not on the default search path. In this case, it may be necessary to manually
specify the path to the graphviz include and/or library directories. To do that use following instructions and install
pygraphviz manually.
```
brew install graphviz
export CFLAGS="-I$(brew --prefix graphviz)/include"
export LDFLAGS="-L$(brew --prefix graphviz)/lib"
pip install pygraphviz
```
## Usage
The `AnndataEnricher` and `AnndataAnalyzer` classes can be used both individually and in conjunction with the `AnndataEnrichmentAnalyzer` wrapper class. The `AnndataEnrichmentAnalyzer` class serves as a convenient way to leverage the functionalities of both `AnndataEnricher` and `AnndataAnalyzer`.
### Using AnndataEnricher and AnndataAnalyzer Individually
You can use the `AnndataEnricher` and `AnndataAnalyzer` classes separately to perform specific tasks on your data. For instance, `AnndataEnricher` facilitates data enrichment, while `AnndataAnalyzer` provides various analysis tools for Anndata objects.
```python
from pandasaurus_cxg.anndata_enricher import AnndataEnricher
ade = AnndataEnricher.from_file_path("test/data/modified_human_kidney.h5ad")
ade.simple_enrichment()
ade.minimal_slim_enrichment(["blood_and_immune_upper_slim"])
```
```python
from pandasaurus_cxg.anndata_analyzer import AnndataAnalyzer
ada = AnndataAnalyzer.from_file_path("./immune_example.h5ad", author_cell_type_list = ['subclass.full', 'subclass.l3', 'subclass.l2', 'subclass.l1', 'class', 'author_cell_type'])
ada.co_annotation_report()
```
### Using AnndataEnrichmentAnalyzer Wrapper
The AnndataEnrichmentAnalyzer class wraps the functionality of both AnndataEnricher and AnndataAnalyzer, offering a seamless way to perform enrichment and analysis in one go.
```python
from pandasaurus_cxg.enrichment_analysis import AnndataEnrichmentAnalyzer
from pandasaurus_cxg.graph_generator.graph_generator import GraphGenerator
aea = AnndataEnrichmentAnalyzer("test/data/modified_human_kidney.h5ad")
aea.contextual_slim_enrichment()
aea.co_annotation_report()
gg = GraphGenerator(aea)
gg.generate_rdf_graph()
gg.set_label_adding_priority(["class", "cell_type", "subclass.l1", "subclass.l1", "subclass.full", "subclass.l2", "subclass.l3"])
gg.add_label_to_terms()
gg.enrich_rdf_graph()
gg.save_rdf_graph(file_name="kidney_new", _format="ttl")
```
More examples and detailed explanation can be found in jupyter notebook given in [Snippets](#Snippets)
## Snippets
https://github.com/INCATools/pandasaurus_cxg/blob/main/walkthrough.ipynb
## Library Documentation
https://incatools.github.io/pandasaurus_cxg/
## Roadmap
https://github.com/INCATools/pandasaurus_cxg/blob/main/ROADMAP.md