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Estimating relative abundances of proteins from shotgun proteomics data.
McIlwain, Sean; Mathews, Michael; Bereman, Michael S; Rubel, Edwin W; MacCoss, Michael J; Noble, William Stafford.
Afiliación
  • McIlwain S; Department of Genome Sciences, University of Washington, Seattle, WA, USA.
BMC Bioinformatics ; 13: 308, 2012 Nov 19.
Article en En | MEDLINE | ID: mdl-23164367
BACKGROUND: Spectral counting methods provide an easy means of identifying proteins with differing abundances between complex mixtures using shotgun proteomics data. The crux spectral-counts command, implemented as part of the Crux software toolkit, implements four previously reported spectral counting methods, the spectral index (SI(N)), the exponentially modified protein abundance index (emPAI), the normalized spectral abundance factor (NSAF), and the distributed normalized spectral abundance factor (dNSAF). RESULTS: We compared the reproducibility and the linearity relative to each protein's abundance of the four spectral counting metrics. Our analysis suggests that NSAF yields the most reproducible counts across technical and biological replicates, and both SI(N) and NSAF achieve the best linearity. CONCLUSIONS: With the crux spectral-counts command, Crux provides open-source modular methods to analyze mass spectrometry data for identifying and now quantifying peptides and proteins. The C++ source code, compiled binaries, spectra and sequence databases are available at http://noble.gs.washington.edu/proj/crux-spectral-counts.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Proteínas / Proteómica Tipo de estudio: Prognostic_studies Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2012 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Proteínas / Proteómica Tipo de estudio: Prognostic_studies Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2012 Tipo del documento: Article País de afiliación: Estados Unidos