pyXLMS 1.3.0

A python package to process protein cross-linking data.

pyXLMS

a python package to process protein cross-linking data

pyXLMS is a python package and web application with graphical user interface that aims to simplify and streamline the intermediate step of connecting crosslink search engine results with down-stream analysis tools, enabling researchers even without bioinformatics knowledge to conduct in-depth crosslink analyses and shifting the focus from data transformation to data interpretation and therefore gaining biological insight. Currently pyXLMS supports input from six different crosslink search engines: MaxLynx (part of MaxQuant), MeroX, MS Annika, pLink 2 and pLink 3, Scout, xiSearch and xiFDR, XlinkX, as well as the mzIdentML format of the HUPO Proteomics Standards Initiative, and a well-documented and human-readable custom tabular format. Down-stream analysis is facilitated by functionality that is directly available within pyXLMS such as validation, annotation, aggregation, and filtering of crosslink-spectrum-matches and crosslinks. In addition, the data can easily be exported to the required data format of the various available down-stream analysis tools such as xiNET, xiVIEW, xiFDR, XlinkDB, xlms-tools, pyMOL (via pyXlinkViewer), ChimeraX (via XMAS), or IMP-X-FDR.

Installation

pyXLMS supports python version 3.7 and greater!

pyXLMS can easily be installed via pip:

pip install pyxlms

Quick Start

After installation you can use pyXLMS in python like this:

This example shows reading of MS Annika crosslink-spectrum-matches and exporting them to xiFDR format for external validation.

>>> import pyXLMS
>>> pr = pyXLMS.parser.read("data/ms_annika/XLpeplib_Beveridge_QEx-HFX_DSS_R1_CSMs.xlsx", engine="MS Annika", crosslinker="DSS")
Reading MS Annika CSMs...: 100%|████████████████████████████████████████████████████████████████████████████████| 826/826 [00:00<00:00, 20731.70it/s]
>>> _ = pyXLMS.transform.summary(pr)
Number of CSMs: 826.0
Number of unique CSMs: 826.0
Number of intra CSMs: 803.0
Number of inter CSMs: 23.0
Number of target-target CSMs: 786.0
Number of target-decoy CSMs: 39.0
Number of decoy-decoy CSMs: 1.0
Minimum CSM score: 1.11
Maximum CSM score: 452.99
>>> _ = pyXLMS.exporter.to_xifdr(pr["crosslink-spectrum-matches"], filename="msannika_CSMs_for_xiFDR.csv")

Web App

The web app is publicly accessible for free via hgb-bin-proteomics.github.io/pyXLMS-app.

Additionally, it can be run locally or self-hosted via:

• Running the streamlit app locally:
  • cd gui
  • pip install -r requirements.txt
  • streamlit run streamlit_app.py
• Building the Docker container yourself:
  • docker build . -f Dockerfile -t pyxlms
  • docker run -p 8501:8501 pyxlms
• or by pulling the provided image from Docker Hub:
  • docker run -p 8501:8501 michabirklbauer/pyxlms:latest

User Guide, Examples and Documentation

• A user guide that documents all available functionality is available via hgb-bin-proteomics.github.io/pyXLMS-docs.
• Example jupyter notebooks can be found in /examples.
• A full documentation of the python package can be accessed via hgb-bin-proteomics.github.io/pyXLMS.

Citing

If you are using pyXLMS please cite the following publication:

• Manuscript in preparation

  (wip)
  

Contact

• [e-mail]
• [e-mail] (primary developer)