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A model for random sampling and estimation of relative protein abundance in shotgun proteomics

Academic Article
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Overview

authors

  • Liu, H. B.
  • Sadygov, R. G.
  • Yates III, John

publication date

  • July 2004

journal

  • Analytical Chemistry  Journal

abstract

  • Proteomic analysis of complex protein mixtures using proteolytic digestion and liquid chromatography in combination with tandem mass spectrometry is a standard approach in biological studies. Data-dependent acquisition is used to automatically acquire tandem mass spectra of peptides eluting into the mass spectrometer. In more complicated mixtures, for example, whole cell lysates, data-dependent acquisition incompletely samples among the peptide ions present rather than acquiring tandem mass spectra for all ions available. We analyzed the sampling process and developed a statistical model to accurately predict the level of sampling expected for mixtures of a specific complexity. The model also predicts how many analyses are required for saturated sampling of a complex protein mixture. For a yeast-soluble cell lysate 10 analyses are required to reach a 95% saturation level on protein identifications based on our model. The statistical model also suggests a relationship between the level of sampling observed for a protein and the relative abundance of the protein in the mixture. We demonstrate a linear dynamic range over 2 orders of magnitude by using the number of spectra (spectral sampling) acquired for each protein.

subject areas

  • Data Collection
  • Models, Statistical
  • Proteins
  • Proteomics
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Identity

International Standard Serial Number (ISSN)

  • 0003-2700

Digital Object Identifier (DOI)

  • 10.1021/ac0498563

PubMed ID

  • 15253663
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Additional Document Info

start page

  • 4193

end page

  • 4201

volume

  • 76

issue

  • 14

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