False discovery rate estimation for cross-linked peptides identified by mass spectrometry

Thomas Walzthoeni; Manfred Claassen; Alexander Leitner; Franz Herzog; Stefan Bohn; Friedrich Förster; Martin Beck; Ruedi Aebersold

doi:10.1038/nmeth.2103

False discovery rate estimation for cross-linked peptides identified by mass spectrometry

Thomas Walzthoeni, Manfred Claassen, Alexander Leitner, Franz Herzog, Stefan Bohn, Friedrich Förster, Martin Beck, Ruedi Aebersold

Research output: Contribution to journal › Article › peer-review

Abstract

The mass spectrometric identification of chemically cross-linked peptides (CXMS) specifies spatial restraints of protein complexes; these values complement data obtained from common structure-determination techniques. Generic methods for determining false discovery rates of cross-linked peptide assignments are currently lacking, thus making data sets from CXMS studies inherently incomparable. Here we describe an automated target-decoy strategy and the software tool xProphet, which solve this problem for large multicomponent protein complexes.

Original language	English
Pages (from-to)	901-903
Number of pages	3
Journal	Nature Methods
Volume	9
Issue number	9
DOIs	https://doi.org/10.1038/nmeth.2103
Publication status	Published - Sept 2012
Externally published	Yes

Research fields

Chemical Crosslinking
Mass spectrometry

IMC Research Focuses

Medical biotechnology

ÖFOS 2012 - Austrian Fields of Study

106037 Proteomics
106041 Structural biology
106044 Systems biology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/nmeth.2103

Cite this

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title = "False discovery rate estimation for cross-linked peptides identified by mass spectrometry",

abstract = "The mass spectrometric identification of chemically cross-linked peptides (CXMS) specifies spatial restraints of protein complexes; these values complement data obtained from common structure-determination techniques. Generic methods for determining false discovery rates of cross-linked peptide assignments are currently lacking, thus making data sets from CXMS studies inherently incomparable. Here we describe an automated target-decoy strategy and the software tool xProphet, which solve this problem for large multicomponent protein complexes.",

author = "Thomas Walzthoeni and Manfred Claassen and Alexander Leitner and Franz Herzog and Stefan Bohn and Friedrich F{\"o}rster and Martin Beck and Ruedi Aebersold",

note = "Funding Information: This work was supported by the European Union 7th Framework project PROSPECTS (Proteomics Specification in Space and Time, grant HEALTH-F4-2008-201648) and ERC advanced grant {\textquoteleft}Proteomics v3.0{\textquoteright} (grant no. 233226) of the European Union to R.A. We thank O. Rinner and A.I. Nesvizhskii for constructive discussions.",

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doi = "10.1038/nmeth.2103",

language = "English",

volume = "9",

pages = "901--903",

journal = "Nature Methods",

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T1 - False discovery rate estimation for cross-linked peptides identified by mass spectrometry

AU - Walzthoeni, Thomas

AU - Claassen, Manfred

AU - Leitner, Alexander

AU - Herzog, Franz

AU - Bohn, Stefan

AU - Förster, Friedrich

AU - Beck, Martin

AU - Aebersold, Ruedi

N1 - Funding Information: This work was supported by the European Union 7th Framework project PROSPECTS (Proteomics Specification in Space and Time, grant HEALTH-F4-2008-201648) and ERC advanced grant ‘Proteomics v3.0’ (grant no. 233226) of the European Union to R.A. We thank O. Rinner and A.I. Nesvizhskii for constructive discussions.

PY - 2012/9

Y1 - 2012/9

N2 - The mass spectrometric identification of chemically cross-linked peptides (CXMS) specifies spatial restraints of protein complexes; these values complement data obtained from common structure-determination techniques. Generic methods for determining false discovery rates of cross-linked peptide assignments are currently lacking, thus making data sets from CXMS studies inherently incomparable. Here we describe an automated target-decoy strategy and the software tool xProphet, which solve this problem for large multicomponent protein complexes.

AB - The mass spectrometric identification of chemically cross-linked peptides (CXMS) specifies spatial restraints of protein complexes; these values complement data obtained from common structure-determination techniques. Generic methods for determining false discovery rates of cross-linked peptide assignments are currently lacking, thus making data sets from CXMS studies inherently incomparable. Here we describe an automated target-decoy strategy and the software tool xProphet, which solve this problem for large multicomponent protein complexes.

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U2 - 10.1038/nmeth.2103

DO - 10.1038/nmeth.2103

M3 - Article

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SN - 1548-7091

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JF - Nature Methods

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False discovery rate estimation for cross-linked peptides identified by mass spectrometry

Abstract

Research fields

IMC Research Focuses

ÖFOS 2012 - Austrian Fields of Study

UN SDGs

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