The galaxy platform for reproducible affinity proteomic mass spectrometry data analysis

Paul A. Stewart, Brent M. Kuenzi, Subina Mehta, Praveen Kumar, James E. Johnson, Pratik Jagtap, Timothy J. Griffin, Eric B. Haura

Research output: Chapter in Book/Report/Conference proceedingChapter

5 Scopus citations

Abstract

Affinity proteomics (AP-MS) is growing in importance for characterizing protein-protein interactions (PPIs) in the form of protein complexes and signaling networks. The AP-MS approach necessitates several different software tools, integrated into reproducible and accessible workflows. However, if the scientist (e.g., a bench biologist) lacks a computational background, then managing large AP-MS datasets can be challenging, manually formatting AP-MS data for input into analysis software can be error-prone, and data visualization involving dozens of variables can be laborious. One solution to address these issues is Galaxy, an open source and web-based platform for developing and deploying user-friendly computational pipelines or workflows. Here, we describe a Galaxy-based platform enabling AP-MS analysis. This platform enables researchers with no prior computational experience to begin with data from a mass spectrometer (e.g., peaklists in mzML format) and perform peak processing, database searching, assignment of interaction confidence scores, and data visualization with a few clicks of a mouse. We provide sample data and a sample workflow with step-by-step instructions to quickly acquaint users with the process.

Original languageEnglish (US)
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages249-261
Number of pages13
DOIs
StatePublished - 2019

Publication series

NameMethods in Molecular Biology
Volume1977
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Bibliographical note

Publisher Copyright:
© Springer Science+Business Media, LLC, part of Springer Nature 2019.

Keywords

  • AP-MS
  • APOSTL
  • Affinity proteomics
  • Affinity purification
  • Galaxy-P

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