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Tuesday, June 28 • 10:20am - 10:40am
An Interactive Tool for Reproducible Analysis of Affinity Proteomics Data

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→ Slides    doi:10.7490/f1000research.1112710.1

Authors:
Brent. M. Kuenzi (1), Adam Borne (2), Jiannong Li (3), Eric B. Haura (2), John Koomen (4), Paul A. Stewart (2), Uwe Rix (1)

Departments of (1) Drug Discovery, (2) Thoracic Oncology, (3) Biostatistics Core Facility, (4) Molecular Oncology, Moffitt Cancer Center, Tampa, FL 33612

Abstract
Understanding protein interactions and how they are altered in cancer is crucial for identifying new drug targets. Purification methods such as tandem affinity purification, affinity enrichment of labeled baits, and drug affinity chromatography have all been combined with mass spectrometry (affinity purification MS or AP-MS) to study protein interactions and complexes in cancer. However, if the scientist (e.g. a bench biologist or analytical chemist) lacks a computational background, then managing large proteomics datasets can be challenging, manually formatting data for input into analysis software can be error-prone, and data visualization involving dozens of variables can be laborious. These difficulties presented an opportunity to develop a solution that could move data from unprocessed AP-MS results to publication-quality figures in a single workflow. Here, we present Automated Processing of SAINT Templated Layouts (APOSTL), a Galaxy-based analysis pipeline for reproducible analysis of AP-MS data, and we demonstrate that this application streamlines the AP-MS data analysis workflow, improving both efficiency and consistency of the process. APOSTL utilizes Significance Analysis of INTeractome (SAINT), popular command-line software for analyzing AP-MS data. APOSTL can process AP-MS results from both MaxQuant and Scaffold, two widely used proteomics software, and APOSTL can create a number of publication-quality visualizations including interactive bubble plots, protein-protein interaction networks through Cytoscape.js integration, and pathway enrichment/gene ontology plots. All visualizations are accomplished through Shiny, an interactive and open-source visualization package for the R programming language. APOSTL is open-source software released under GPLv3, and it is freely available on the Galaxy Tool Shed and GitHub. 

Speakers
avatar for Paul A. Stewart

Paul A. Stewart

Moffitt Cancer Center



Attendees (23)