Protocol

Proteomics in Systems Biology

Volume 1394 of the series Methods in Molecular Biology pp 261-273

Date:

Interpretation of Quantitative Shotgun Proteomic Data

  • Elise AasebøAffiliated withProteomics Unit, Department of Biomedicine, University of Bergen
  • , Frode S. BervenAffiliated withProteomics Unit, Department of Biomedicine, University of BergenKG Jebsen Centre for Multiple Sclerosis Research, Department of Clinical Medicine, University of BergenNorwegian Multiple Sclerosis Competence Centre, Department of Neurology, Haukeland University Hospital
  • , Frode SelheimAffiliated withProteomics Unit, Department of Biomedicine, University of Bergen
  • , Harald BarsnesAffiliated withProteomics Unit, Department of Biomedicine, University of BergenKG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen
  • , Marc VaudelAffiliated withProteomics Unit, Department of Biomedicine, University of Bergen Email author 

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Abstract

In quantitative proteomics, large lists of identified and quantified proteins are used to answer biological questions in a systemic approach. However, working with such extensive datasets can be challenging, especially when complex experimental designs are involved. Here, we demonstrate how to post-process large quantitative datasets, detect proteins of interest, and annotate the data with biological knowledge. The protocol presented can be achieved without advanced computational knowledge thanks to the user-friendly Perseus interface (available from the MaxQuant website, www.​maxquant.​org). Various visualization techniques facilitating the interpretation of quantitative results in complex biological systems are also highlighted.

Key words

Quantification Data interpretation Perseus Data post-processing