English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  The MaxQuant computational platform for mass spectrometry-based shotgun proteomics

Tyanova, S., Temu, T., & Cox, J. (2016). The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nature Protocols, 11(12), 2301-2319. doi:10.1038/nprot.2016.136.

Item is

Files

show Files

Locators

show
hide
Description:
-
OA-Status:

Creators

show
hide
 Creators:
Tyanova, Stefka1, Author           
Temu, Tikira1, Author           
Cox, Jürgen1, Author           
Affiliations:
1Cox, Jürgen / Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society, ou_2063284              

Content

show
hide
Free keywords: COMPLEX PROTEIN MIXTURES; QUANTITATIVE PROTEOMICS; PEPTIDE IDENTIFICATION; DATA SETS; QUANTIFICATION; EXPRESSION; SPECTRA; MS/MS; DISSOCIATION; STRATEGYBiochemistry & Molecular Biology;
 Abstract: 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.

Details

show
hide
Language(s): eng - English
 Dates: 2016-10-272016
 Publication Status: Issued
 Pages: 19
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: ISI: 000386976800001
DOI: 10.1038/nprot.2016.136
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Nature Protocols
  Other : Nat. Protoc.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 11 (12) Sequence Number: - Start / End Page: 2301 - 2319 Identifier: ISSN: 1750-2799
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000223800_1