PepNet

Visit https://denovo.predfull.com/ to try online prediction

The state of the art Deep CNN neural network for de novo sequencing of tandem mass spectra, currently works on unmodified HCD spectra of charges 1+ to 4+.

Update History

  • 2022.11.28: Revised version.
  • 2021.12.28: First version.

Method

Based on the structure of the residual convolutional networks. Current precision (bin size): 0.1 Th.

model

How to use

After clone this project, you should download the pre-trained model (model.h5) from zenodo.org and place it into PepNet's folder.

Important Notes

  • Will only output unmodification sequences.
  • This model assumes a FIXED carbamidomethyl on C
  • The length of output peptides are limited to =< 30

Required Packages

Recommend to install dependency via Anaconda

  • Python >= 3.7
  • Tensorflow >= 2.5.0
  • Pandas >= 0.20
  • pyteomics

Output format

Sample output looks like:

TITLE DENOVO Score PPM Difference Positional Score
spectra 1 LALYCHQLNLCSK 1.0000 -3.8919184 [1.0, 0.9999956, 1.0, 1.0, 1.0, 1.0, 0.99999976, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
spectra 2 HEELMLGDPCLK 1.0000 4.207922 [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.99999976, 1.0]
spectra 3 AGLVGPEFHEK 1.0000 0.54602236 [1.0, 1.0, 1.0, 1.0, 1.0, 0.99999917, 1.0, 1.0, 1.0, 1.0, 1.0]

Usage

Simply run:

python denovo.py --input example.mgf --model model.h5 --output example_prediction.tsv

The output file is in MGF format

  • --input: the input mgf file
  • --output: the output file path
  • --model: the pretrained model

Prediction Examples

We provide sample data on DOI for you to evaluate the sequencing performance. The example.mgf file on google drive contains ground truth spectra (randomly sampled from NIST Human Synthetic Peptide Spectral Library), while the example.tsv file contains pre-run predictions.

Train this model

See train.py for sample training codes

Related works

Also, Visit https://www.predfull.com/ to check our previous project on full spectrum prediction