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The MaxQuant computational platform for mass spectrometry-based shotgun proteomics
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The MaxQuant computational platform for mass spectrometry-based shotgun proteomics
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Journal Article
The MaxQuant computational platform for mass spectrometry-based shotgun proteomics
2016
Overview
MaxQuant is a platform for mass spectrometry-based proteomics data analysis. It includes a peptide database search engine, called Andromeda, and expanding capability to handle data from most quantitative proteomics experiments.
MaxQuant is one of the most frequently used platforms for mass-spectrometry (MS)-based proteomics data analysis. Since its first release in 2008, it has grown substantially in functionality and can be used in conjunction with more MS platforms. Here we present an updated protocol covering the most important basic computational workflows, including those designed for quantitative label-free proteomics, MS1-level labeling and isobaric labeling techniques. This protocol presents a complete description of the parameters used in MaxQuant, as well as of the configuration options of its integrated search engine, Andromeda. This protocol update describes an adaptation of an existing protocol that substantially modifies the technique. Important concepts of shotgun proteomics and their implementation in MaxQuant are briefly reviewed, including different quantification strategies and the control of false-discovery rates (FDRs), as well as the analysis of post-translational modifications (PTMs). The MaxQuant output tables, which contain information about quantification of proteins and PTMs, are explained in detail. Furthermore, we provide a short version of the workflow that is applicable to data sets with simple and standard experimental designs. The MaxQuant algorithms are efficiently parallelized on multiple processors and scale well from desktop computers to servers with many cores. The software is written in C# and is freely available at
http://www.maxquant.org
.
Publisher
Nature Publishing Group UK,Nature Publishing Group
Subject
