Data-Driven Gene Regulatory Network Inference
Project description
GReNaDIne: Gene Regulatory Network Data-driven Inference
This Python 3.7 package allows to infer Gene Regulatory Networks through several Data-driven methods. Pre-processing and evaluation methods are also included.
Dependencies
pip install numpy
version 1.16.2pip install pandas
version 0.24.2pip install matplotlib
version 3.0.3pip install joblib
version 0.13.2pip install Cython
version 0.29.6pip install sklearn
version 0.20.3pip install pandas
version 0.24.2pip install pot
version 0.5.1 POT is not included in the automatic dependencies install You have to install it if you want to use columns_matrix_OT_norm() normalization function. The other functions of the package do not need POT.pip install rpy2
version 3.0.2 rpy2 is not included in the automatic dependencies install You have to install it if you want to use DEseq2() normalization function. The other functions of the package do not need rpy2.
Installation:
pip install GReNaDIne
Tutorials:
Check the jupyter notebook tutorials located in the tutorial folder
Infer_dream5_E_coli_GRN_using_GENIE3.ipynb
to infer GRNs using the GENIE3 method (random forest regression)Infer_dream5_E_coli_GRN_using_SVMs.ipynb
to infer GRNs using the SVM method (SVM classification)
Authors:
For bug reports and feedback do not hesitate to contact the authors
Maintainer:
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