A python package to facilitate Organellar profiling
Project description
The grassp (GRaph-based Analysis of Subcellular/Spatial Proteomics) python module enables fast, flexible and scalable analysis of subcellular proteomics datasets.
It uses the anndata format to store mass-spec data and analysis results and scanpy for many of the dimensionality reduction and visualization functions.
grassp enables
- Reading the ouput format of most mass-spectrometry search engines (using protdata)
- Calculating subcellular enrichment profiles of proteins for different experimental protocols
- Annotating the subcellular location of proteins in an unsupervised and semi-supervised manner
- Detecting proteins at the interface of organelles
- Detecting multi-localizing proteins (work in progress)
- Detecting re-localizing proteins between conditions (work in progress)
- Combining multiple subcellular proteomics datasets
- Assessing subcellular resolution
- Finding the optimal experimental design for future experiments based on simulations
- Integration of multiple modalities (e.g. Lipidomics) (work in progress)
Please refer to the documentation for reference to individual functions and tutorials.
Installation
grassp can be installed via pip from PyPI with:
pip install grassp
For details on installation, please see the install section of the documentation.
Contributing
If you'd like to contribute to grassp please feel free to look at our contribution guide and open a Pull request.
Authors
grassp is created and maintained by the Computational Biology Platform at the Chan Zuckerberg Biohub San Francisco. For details, see the Contributors page.
To get in touch please use the GihHub issues page.
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