Label-free quantitative shotgun proteomics using normalized spectral abundance factors

Karlie A. Neilson, Tim Keighley, Dana Pascovici, Brett Cooke, Paul A. Haynes

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    54 Citations (Scopus)

    Abstract

    In this chapter we describe the work fl ow used in our laboratory for label-free quantitative shotgun proteomics based on spectral counting. The main tools used are a series of R modules known collectively as the Scrappy program. We describe how to go from peptide to spectrum matching in a shotgun proteomics experiment using the XTandem algorithm, to simultaneous quanti fi cation of up to thousands of proteins, using normalized spectral abundance factors. The outputs of the software are described in detail, with illustrative examples provided for some of the graphical images generated. While it is not strictly within the scope of this chapter, some consideration is given to how best to extract meaningful biological information from quantitative shotgun proteomics data outputs.

    Original languageEnglish
    Title of host publicationProteomics for Biomarker Discovery
    EditorsMing Zhou, Timothy Veenstra
    Place of PublicationNew York
    PublisherHumana Press
    Pages205-222
    Number of pages18
    ISBN (Electronic)9781627033602
    ISBN (Print)9781627033596
    DOIs
    Publication statusPublished - 2013

    Publication series

    NameMethods in Molecular Biology: Methods and Protocols
    Volume1002
    ISSN (Print)1064-3745

    Fingerprint

    Dive into the research topics of 'Label-free quantitative shotgun proteomics using normalized spectral abundance factors'. Together they form a unique fingerprint.

    Cite this