A v-SVR based noise constrained Recursive Feature Extraction algorithm for robust deconvolution of cell-types mixture from molecular signatures in python
Since the significant impact of immunotherapy in cancer, the estimation of the immune cell-type proportions present in a tumor becomes crucial. Currently, the deconvolution of the cell mixture content of a tumor is carried out by different analytic tools, yet the accuracy of inferred cell type proportions has room for improvement. We improve tumor immune environment characterization developing MIXTURE, an analytical method based on a noise constrained recursive variable selection for a support vector regression
The MIXTURE dash App has been only tested on Linux. The Mixture Package code was tested on Linux, Windows and Mac. On windows only one CPU core is allowed.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
The current "functional like" version of the software requires the following libraries, however, this package download automatically yours dependencies
- python3 >= 3.6
- pip3
- xlrd
- scikit-learn
- openpyxl
- pandas
- numpy
- multiprocessing
- joblib
Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.
- Elmer Andrés Fernández - Initial work - CONICET, Universidad Catolica de Cordoba - Profile
- Miranda Matias Samuel - Developer - Universidad Catolica de Cordoba
This project is licensed under the MIT License - see the LICENSE.md file for details