pyXiAnnotator

Python wrapper around xiAnnotator MS spectra annotation for linear and crosslinked peptides with additional data analysis features.

Requirements

The xiAnnotator uses Java. The python wrapper requires following packages.

requests
JPype1
memoized-property
numpy
pytest
python_version=3.7

Build

Clone repository and build. The build method below is deprecated but still works.

git clone https://github.com/Rappsilber-Laboratory/pyXiAnnotator.git
cd pyXiAnnotator/
python setup.py sdist bdist_wheel

Installation

Use the package manager pip to install the wheel.

pip install dist/pyxiannotator-0.3.5-py3-none-any.whl

Usage

Pseudo code example

import pyxiannotator
import pandas as pd
import os
import pyteomics

# initialise pyxiannotator
annotator = pyxiannotator.XiAnnotator.XiAnnotatorLocal(java_home_dir='/path/to/jdk/', jvmargs="-Xmx800M")

# read file with crosslinked peptide spectrum matches
csm_df = pd.read_csv(csm_file)

# initialise mgf file readers
mgf_readers = {os.path.basename(f): pyteomics.mgf.read(f) for f in glob.glob('path/to/mgf/*.mgf')}


for i, psm in psm_df.iterrows():
    # get the spectrum id
    scan_id = psm[scan_id_column]

    # get the spectrum's peak list file
    mgf_file = psm[peak_list_file_name_column]

    # get the spectrum
    spectrum = mgf_readers[mgf_file].get_by_id(scan_id)

    # get the spectrum's peptide
    pep = pyxiannotator.AnnotatedSpectrum.Peptide(
        pep_seq1=psm['PepSeq1'],
        pep_seq2=psm['PepSeq2'],
        link_pos1=psm['LinkPos1'],
        link_pos2=psm['LinkPos2'],
    )

    peak_list = list(zip(spectrum['m/z array'], spectrum['intensity array']))

    # create the annotation request
    annotation_request = annotator.create_json_annotation_request(
        peak_list=peak_list,
        peptide=pep,
        precursor_charge=int(psm['Charge']),
        precursor_mz=float(psm['ExpMz']),
        fragment_types=fragment_types,
        fragment_tolerance_ppm=frag_ppm,
        fragment_tolerance_abs=frag_da,
        cross_linker=crosslinker,
        custom_settings=custom_settings,
        modifications=modifications
    )

    # annotate
    annotator.request_annotation_json(annotation_request)

    # retrieve the annotated spectrum 
    annotated_spectrum = annotator.get_annotated_spectrum()