PEP2CCS

The PEP2CCS is a deep learning model designed to predict CCS. This model integrates enhanced physical features of peptides, thereby improving the accuracy of CCS predictions. You can quickly get started with the PEP2CCS according to the following instructions.

Authors: Zhimeng Tian, Zizheng Nie, Yong Zhang, Daming Zhu and Xuefeng Cui*
    - *: To whom correspondence should be addressed.
Contact: xfcui@email.sdu.edu.cn

Installation

Create virtual environment and install packages:

chmod +x run_setup.sh
bash ./run_setup.sh
conda activate PEP2CCS

Quick start

Get clone

Clone this repository by:

git clone https://github.com/xfcui/PEP2CCS.git

Usage

If you want to run our model on your own data, you need to provide the file.

Data preparation

After creating a virtual environment, you need to prepare data and trained model. We provide a sample data in the data directory. We also provide the trained model under the checkpoint/model.pt.

Predict peptide ccs

chmod +x run_prediction.sh
bash ./run_prediction.sh /path_to_test.csv

# The test code is as follows:
chmod +x run_prediction.sh
bash ./run_prediction.sh ./src/data/test_data.csv

Reproduction of the original experiments

Exp1: Performance of PEP2CCS

chmod +x ./src/Exp1/run.sh
bash ./src/Exp1/run.sh

Exp2: The function of charge state

chmod +x ./src/Exp2/run.sh
bash ./src/Exp2/run.sh

Exp3: The function of m/z and length

chmod +x ./src/Exp3/run.sh
bash ./src/Exp3/run.sh

Exp4: Application of m/z

chmod +x ./src/Exp4/run.sh
bash ./src/Exp4/run.sh

Exp5: The function of Mix Pooling

chmod +x ./src/Exp5/run.sh
bash ./src/Exp5/run.sh