Metadata-Version: 2.1
Name: MOBiceps
Version: 0.1.4
Summary: Python tools for Mass Spectrometry and Omics data.
Home-page: https://github.com/JensSettelmeier/MOBiceps
Author: Jens Settelmeier
Author-email: jenssettelmeier@googlemail.com
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3.8
Requires-Python: ==3.8.*
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: joblib (==1.2.0)
Requires-Dist: numpy (==1.21.6)
Requires-Dist: pandas (==1.4.1)
Requires-Dist: seaborn (==0.11.2)
Requires-Dist: yellowbrick (==1.5)
Requires-Dist: scikit-learn (==1.2.1)
Requires-Dist: scipy (==1.8.1)
Requires-Dist: scikit-image (==0.19.2)
Requires-Dist: matplotlib (==3.5.1)
Requires-Dist: shap (==0.41.0)
Requires-Dist: xgboost (==1.6.2)
Requires-Dist: tqdm (==4.63.0)
Requires-Dist: pyopenms (==2.7.0)
Requires-Dist: numba (==0.55.1)
Requires-Dist: torch (==1.13.1)
Requires-Dist: torchvision (==0.14.1)
Requires-Dist: torchaudio (==0.13.1)
Requires-Dist: umap-learn (==0.5.3)
Requires-Dist: statsmodels (==0.13.2)

# MOBiceps
![MOBicpes logo](./images/MOBiceps.png)
MOBiceps is a collection of python functions for omics and mass spectrometry data. It is the working arm of [MOAgent](https://github.com/wollscheidlab/MOAgent). An early version of its core function featureSelector.py was first time applied in the work [Nature Communications, 2023](https://www.nature.com/articles/s41467-023-42101-z) to identify phenotype-specific proteins in myeloproliferative neoplasms (blood cancer).
If you have any questions please do not hesitate to contact jsettelmeier@ethz.ch

## Basic instructions

You can use MOBiceps by cloning the repo to your local machine using

```bash
$ git clone https://github.com/wollscheidlab/MOBiceps.git
```
or using the python package distribution system pip via

```bash
$ pip install MOBiceps
```

## Notes
Developed and tested under python 3.8. 
