Statistical inference from multiple iTRAQ experiments without using common reference standards

Shelley M. Herbrich, Robert N. Cole, Keith P. West, Kerry Schulze, James D. Yager, John D. Groopman, Parul Christian, Lee Wu, Robert N. O'Meally, Damon H. May, Martin W. McIntosh, Ingo Ruczinski

Research output: Contribution to journalArticlepeer-review

84 Scopus citations


Isobaric tags for relative and absolute quantitation (iTRAQ) is a prominent mass spectrometry technology for protein identification and quantification that is capable of analyzing multiple samples in a single experiment. Frequently, iTRAQ experiments are carried out using an aliquot from a pool of all samples, or "masterpool", in one of the channels as a reference sample standard to estimate protein relative abundances in the biological samples and to combine abundance estimates from multiple experiments. In this manuscript, we show that using a masterpool is counterproductive. We obtain more precise estimates of protein relative abundance by using the available biological data instead of the masterpool and do not need to occupy a channel that could otherwise be used for another biological sample. In addition, we introduce a simple statistical method to associate proteomic data from multiple iTRAQ experiments with a numeric response and show that this approach is more powerful than the conventionally employed masterpool-based approach. We illustrate our methods using data from four replicate iTRAQ experiments on aliquots of the same pool of plasma samples and from a 406-sample project designed to identify plasma proteins that covary with nutrient concentrations in chronically undernourished children from South Asia.

Original languageEnglish (US)
Pages (from-to)594-604
Number of pages11
JournalJournal of proteome research
Issue number2
StatePublished - Feb 1 2013


  • Mass spectrometry
  • experimental design
  • iTRAQ
  • statistical analysis

ASJC Scopus subject areas

  • Biochemistry
  • Chemistry(all)


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