RT Journal Article
T1 General statistical framework for quantitative proteomics by stable isotope labeling.
A1 Navarro, Pedro
A1 Trevisan Herraz, Marco
A1 Bonzon Kulichenko, Elena
A1 Núñez, Estefanía
A1 Martínez Acedo, Pablo
A1 Pérez Hernández, Daniel
A1 Jorge, Inmaculada
A1 Mesa, Raquel
A1 Calvo, Enrique
A1 Carrascal, Montserrat
A1 Hernáez, María Luisa
A1 García, Fernando
A1 Bárcena, José Antonio
A1 Ashman, Keith
A1 Abian, Joaquín
A1 Gil, Concha
A1 Redondo, Juan Miguel
A1 Vázquez, Jesús
AB The combination of stable isotope labeling (SIL) with mass spectrometry (MS) allows comparison of the abundance of thousands of proteins in complex mixtures. However, interpretation of the large data sets generated by these techniques remains a challenge because appropriate statistical standards are lacking. Here, we present a generally applicable model that accurately explains the behavior of data obtained using current SIL approaches, including (18)O, iTRAQ, and SILAC labeling, and different MS instruments. The model decomposes the total technical variance into the spectral, peptide, and protein variance components, and its general validity was demonstrated by confronting 48 experimental distributions against 18 different null hypotheses. In addition to its general applicability, the performance of the algorithm was at least similar than that of other existing methods. The model also provides a general framework to integrate quantitative and error information fully, allowing a comparative analysis of the results obtained from different SIL experiments. The model was applied to the global analysis of protein alterations induced by low H₂O₂ concentrations in yeast, demonstrating the increased statistical power that may be achieved by rigorous data integration. Our results highlight the importance of establishing an adequate and validated statistical framework for the analysis of high-throughput data.
PB American Chemical Society
SN 1535-3907
YR 2014
FD 2014-01-31
LK https://hdl.handle.net/20.500.14352/34918
UL https://hdl.handle.net/20.500.14352/34918
LA eng
NO Spanish Ministry of Science and Education
NO Comunidad de Madrid
NO Red Temática de Investigación Cooperativa en Enfermedades Cardiovasculares
DS Docta Complutense
RD 7 abr 2025