Commit 9de5d340 authored by wangys_biolab's avatar wangys_biolab

Update README.md

parent 290db156
......@@ -28,24 +28,32 @@ Before running Effector-GAN, users should make sure all the following packages a
Activate conda environment:
`source activate Effector-GAN`
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`
other packages
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
pip3 install sklearn
###**prPred**
##**Effector-GAN**
git clone git@github.com:Wangys-prog/prPred.git
......@@ -74,20 +82,15 @@ prPred -h
> R_protein_possibility.fasta
## For split_fasta.py
**Analyze your sequences one by one**
**Before using the script,please add prPred into into environment variables**
python split_fasta.py -i your fasta file
## For windows 10 or later
## WGAN.py
Synthetic protein feature samples based on generative adversarial networks
**Download Ubuntu xx.x LTS from Microsoft Store**
## CTST2.py
Effector-GAN uses the leave-one-out cross-validation (LOOCV) method based on K nearest neighbor algorithm (KNN; K=1) classifier to evaluate the optimal synthetic protein feature samples, which are used to augment the original positive training samples
cd ../../
cd mnt/x/xxxx/xxxx/
git clone git@github.com:Wangys-prog/prPred.git
cd mnt/x/xxxx/xxxx/prPred/
## **If you use prPred, please cite:**
(1) Wang Y, Wang P, Guo Y, et al. prPred: A Predictor to Identify Plant Resistance Proteins by Incorporating k-Spaced Amino Acid (Group) Pairs[J]. Frontiers in bioengineering and biotechnology, 2021, 8: 1593.
......
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