Guidelines for reporting quantitative mass spectrometry based experiments in proteomics

Salvador Martínez-Bartolomé, Eric W. Deutsch, Pierre Alain Binz, Andrew R. Jones, Martin Eisenacher, Gerhard Mayer, Alex Campos, Francesc Canals, Joan Josep Bech-Serra, Montserrat Carrascal, Marina Gay, Alberto Paradela, Rosana Navajas, Miguel Marcilla, María Luisa Hernáez, María Dolores Gutiérrez-Blázquez, Luis Felipe Clemente Velarde, Kerman Aloria, Jabier Beaskoetxea, J. Alberto Medina-AunonJuan P. Albar

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    35 Citations (Scopus)

    Abstract

    Mass spectrometry is already a well-established protein identification tool and recent methodological and technological developments have also made possible the extraction of quantitative data of protein abundance in large-scale studies. Several strategies for absolute and relative quantitative proteomics and the statistical assessment of quantifications are possible, each having specific measurements and therefore, different data analysis workflows.The guidelines for Mass Spectrometry Quantification allow the description of a wide range of quantitative approaches, including labeled and label-free techniques and also targeted approaches such as Selected Reaction Monitoring (SRM). Biological significance: The HUPO Proteomics Standards Initiative (HUPO-PSI) has invested considerable efforts to improve the standardization of proteomics data handling, representation and sharing through the development of data standards, reporting guidelines, controlled vocabularies and tooling. In this manuscript, we describe a key output from the HUPO-PSI-namely the MIAPE Quant guidelines, which have developed in parallel with the corresponding data exchange format mzQuantML [1]. The MIAPE Quant guidelines describe the HUPO-PSI proposal concerning the minimum information to be reported when a quantitative data set, derived from mass spectrometry (MS), is submitted to a database or as supplementary information to a journal. The guidelines have been developed with input from a broad spectrum of stakeholders in the proteomics field to represent a true consensus view of the most important data types and metadata, required for a quantitative experiment to be analyzed critically or a data analysis pipeline to be reproduced. It is anticipated that they will influence or be directly adopted as part of journal guidelines for publication and by public proteomics databases and thus may have an impact on proteomics laboratories across the world. This article is part of a Special Issue entitled: Standardization and Quality Control. © 2013 Elsevier B.V.
    Original languageEnglish
    Pages (from-to)84-88
    JournalJournal of Proteomics
    Volume95
    DOIs
    Publication statusPublished - 16 Dec 2013

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