title: Protein quantitation using iTRAQ: Review on the sources of variations and analysis of nonrandom missingness.
abstract: As a technique that allows simultaneous quantitation of proteins in multiple samples, iTRAQ (isobaric Tags for Relative and Absolute Quantitation) has gained increased interest and applications in proteomics research. Despite its success, iTRAQ data present a number of statistical challenges even after the proteins and peptides are identified and the peak areas of the reported ions are estimated for peptide intensities. In this article, we review recent studies on the analysis of iTRAQ data, the computation problems involved and the nonrandom missingness in the iTRAQ data.
authors.affiliation: Department of Mathematics and Statistics, Georgia State University, 30 Pryor Street, Atlanta, GA 30303, USA.
authors.forename: Ruiyan
authors.initials: R
authors.lastname: Luo
authors.forename: Hongyu
authors.initials: H
authors.lastname: Zhao
keywords: ANOVA; Bayesian hierarchical model; Mass spectrometry; Nonrandom missing; iTRAQ