PredFull

Visit http://predfull.com/ to try online prediction

This work was published on Analytical Chemistry: Full-Spectrum Prediction of Peptides Tandem Mass Spectra using Deep Neural Network

Kaiyuan Liu, Sujun Li, Lei Wang, Yuzhen Ye, Haixu Tang

Update History

• 2020.05.25: Support predicting non-tryptic peptides
• 2019.09.01: First version

Method

Based on the structure of the residual convolutional networks. Current precision: 0.1 Th.

How to use

Important Notes

• This model support only UNMODIFIED peptides (for now, at least)
• This model assume a FIXED carbamidomethyl on C
• The length of input peptides are limited to =< 30
• The prediction will NOT output peaks with M/z > 2000

Required Packages

Recommend to install dependency via Anaconda

• Tensorflow >= 2.0.0
• Pandas >= 0.20
• pyteomics
• lxml

Input format

The required input format is TSV, with following columns:

Peptide	Charge	Type	NCE
AAAAAAAAAVSR	2	HCD	25
AAGAAESEEDFLR	2	HCD	25
AAPAPTASSTININTSTSK	2	HCD	25

Apparently, 'Peptide' and 'Charge' columns mean what it says. The 'Type' must be HCD or ETD (in uppercase). NCE means normalized collision energy, set to 25 or 30 if you don't care. Check example.tsv for examples.

Usage

Simply run:

python predfull.py --input example.tsv --model pm.h5 --output example.mgf

The output file is in MGF format

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

Prediction Examples