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 language | English (US) |
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Title of host publication | Methods in Molecular Biology |
Publisher | Humana Press Inc. |
Pages | 249-261 |
Number of pages | 13 |
DOIs | |
State | Published - 2019 |
Publication series
Name | Methods in Molecular Biology |
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Volume | 1977 |
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