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wangys_biolab
effector-gan
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21cbab90
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21cbab90
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Feb 15, 2022
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wangys_biolab
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21cbab90
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@@ -6,30 +6,44 @@ Effector-GAN: prediction of fungal effector proteins based on pre-trained deep r
Effector-GAN is an open-source Python-based toolkit, which operates depending on the Python environment (Python Version 3.7).
Before running Effector-GAN, users should make sure all the following packages are installed in their Python environment:
joblib==1.0.1
tape_proteins==0.4
torch==1.2.0+cpu
numpy==1.19.2
pandas==1.2.0
Bio==0.4.1
tape==1.0
sklearn
Before running Effector-GAN, users should make sure all the following packages are installed in their Python environment.
## **Prerequisites**
###
1.
**iFeature**
### **iFeature**
To obtain iFeature, please download from https://github.com/Superzchen/iFeature/.
**Add iFeature into environment variables (~/.bashrc)**
` export PATH=$PATH:/xxxx/xxxx/xxxxx/iFeature`
## **Installation**
Create an Python3.7 environment using conda:
`conda create -n Effector-GAN python=3.7`
Activate conda environment:
`source activate Effector-GAN`
pip3 install joblib==1.0.1
pip3 install tape_proteins==0.4
pip3 install numpy==1.19.2
pip3 install pandas==1.2.0
pip3 install Bio==0.4.1
sklearn
#### For python3.7
#### If you have GPU # CUDA 9.2
pip install torch==1.2.0 torchvision==0.4.0
#### If you have GPU CUDA 10.0
pip install torch==1.2.0+cu92 torchvision==0.4.0+cu92 -f https://download.pytorch.org/whl/torch_stable.html
#### CPU Only python3.7
pip install torch==1.2.0+cpu torchvision==0.4.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
###**prPred**
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