Update README.md

README.md

@@ -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**