MaxQuant for in-depth analysis of large SILAC datasets

Stefka Tyanova; Matthias Mann; Jürgen Cox

doi:10.1007/978-1-4939-1142-4_24

MaxQuant for in-depth analysis of large SILAC datasets

Methods Mol Biol. 2014:1188:351-64. doi: 10.1007/978-1-4939-1142-4_24.

Authors

Stefka Tyanova¹, Matthias Mann, Jürgen Cox

Affiliation

¹ Department for Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, 82152, Martinsried, Germany.

PMID: 25059623
DOI: 10.1007/978-1-4939-1142-4_24

Abstract

Proteomics experiments can generate very large volumes of data, in particular in situations where within one experimental design many samples are compared to each other, possibly in combination with pre-fractionation of samples prior to LC-MS analysis. Here we provide a step-by-step protocol explaining how the current MaxQuant version can be used to analyze large SILAC-labeling datasets in an efficient way.

MeSH terms

Amino Acids / chemistry*
Cells, Cultured
Chromatography, Liquid
Computational Biology / methods*
Isotope Labeling / methods*
Mass Spectrometry
Proteomics / methods*
Software*
Statistics as Topic / methods*
User-Computer Interface

Substances

Amino Acids